serpro69 · May 6, 2026 20:21
diff --git a/session-b5ee5362.jsonl b/session-b5ee5362.jsonl
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Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements).\nTRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a Claude feature (caching, thinking, compaction, tool use, batch, files, citations, memory) or model (Opus/Sonnet/Haiku) in a file; questions about prompt caching / cache hit rate in an Anthropic SDK project.\nSKIP: file imports `openai`/other-provider SDK, filename like `*-openai.py`/`*-generic.py`, provider-neutral code, general programming/ML.\n- kk:design: Use in pre-implementation (idea-to-design) stages to understand spec/requirements and create a correct implementation plan before writing actual code.\nTurns ideas into a fully-formed PRD/design/specification and implementation-plan. Creates design docs and task lists in docs/wip/.\n- kk:document: After implementing a new feature or fixing a bug, make sure to document the changes.\nUse when writing documentation, after finishing the implementation phase for a feature or a bug-fix.\n- kk:review-design: Review design and implementation docs produced by design. Evaluates document quality, internal consistency, and technical soundness.\nUse after design completes and before starting implement.\n- kk:chain-of-verification: Apply Chain-of-Verification (CoVe) prompting to improve response accuracy through self-verification.\nUse when complex questions require fact-checking, technical accuracy, or multi-step reasoning.\n- kk:merge-docs: Compare and merge two design docs for the same feature into a single source of truth.\nUse when you have competing or complementary design/implementation docs (e.g. from separate design runs) that need reconciling into one unified document.\n- kk:dependency-handling: TRIGGER when: adding or upgrading any dependency — library, SDK, framework, API, IaC API version (K8s/Terraform/Helm), CRD, or container image. Use BEFORE writing the call. 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 {"type":"file-history-snapshot","messageId":"5fccac32-8aef-4d7c-abc9-7bb62c7d9fbd","snapshot":{"messageId":"5fccac32-8aef-4d7c-abc9-7bb62c7d9fbd","trackedFileBackups":{},"timestamp":"2026-04-23T18:04:44.249Z"},"isSnapshotUpdate":false}
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 {"parentUuid":"a6c24124-5b10-4cd4-afe4-fcd943d2effc","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01T3JKzt6p8sBYQJvyMhaeS7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JT1r4shhzYJr2xURdqGUEt","name":"mcp__pal__chat","input":{"prompt":"I'm building a feature called \"sessionflow RAG\" for `capy` — an MCP server / Claude Code plugin that indexes tool outputs into SQLite FTS5 with BM25 search to prevent context window flooding.\n\n**Current architecture context:**\n- capy has an FTS5 knowledge base (`internal/store/`) with source-labeled chunks, BM25 search with three-tier fallback (Porter stemming, trigram, fuzzy Levenshtein)\n- It has hook infrastructure (`internal/hook/`) including `sessionend.go` for Claude Code session-end hooks\n- Chunks have a `source` label and configurable TTL for cleanup\n- capy operates within the boundary of a single project (each project gets its own DB)\n\n**The feature (GitHub issue #24):**\nClaude Code stores conversation sessions as JSONL in `~/.claude/projects/`. These sessions contain valuable decisions, rationale, and context that's lost after conversation ends. We want to make them searchable.\n\n**Requirements from the user:**\n\n1. **What to index:** Only human/assistant text messages. Skip tool results, file edits, and any session that had no meaningful conversation (e.g. someone just ran `/config` and closed). Filter out Claude Code inner-workings noise.\n\n2. **Ingestion trigger:** Automatic via session-end hook. NOT exposed as an MCP tool — the assistant shouldn't need to think about this.\n\n3. **Chunking:** Sessions need to be searchable. Question is how to chunk — by individual turns, groups of turns, topic segments?\n\n4. **TTL:** Longer TTL than normal indexed content. Sessions show \"progress over time\" for a project and have lasting value.\n\n5. **Scope:** More structured than just dumping text. But tagging by project is irrelevant since capy already operates per-project.\n\n**My questions for you:**\n\nA. **Chunking strategy:** What's the right granularity? Individual turn pairs (human+assistant) lose conversational context. Whole sessions are too coarse for BM25. Sliding windows of N turns with overlap? Topic-based segmentation? What works best with BM25/FTS5?\n\nB. **Filtering heuristics:** How do we reliably detect \"non-meaningful\" sessions? Minimum turn count? Minimum assistant response length? Presence of certain patterns (like `/config`, `/help` only)?\n\nC. **Structured metadata:** What metadata should we extract and store alongside chunks? Session ID, timestamp, turn range — what else would make searches more useful?\n\nD. **Dedup and incremental indexing:** Sessions that are already indexed shouldn't be re-processed. What's the cleanest approach — track indexed session file hashes? Modification times? A separate tracking table?\n\nE. **Session file format:** Claude Code JSONL format — what are the key message types and fields we need to parse? What's the schema?\n\nF. **Any gotchas or design risks** you see with this approach?\n\nI want a thorough second opinion before we start designing.","model":"gemini-3.1-pro-preview","thinking_mode":"high","temperature":0.4,"absolute_file_paths":["/home/sergio/Projects/personal/capy/internal/store/schema.go","/home/sergio/Projects/personal/capy/internal/store/types.go","/home/sergio/Projects/personal/capy/internal/store/chunk.go","/home/sergio/Projects/personal/capy/internal/store/index.go","/home/sergio/Projects/personal/capy/internal/store/search.go","/home/sergio/Projects/personal/capy/internal/store/cleanup.go","/home/sergio/Projects/personal/capy/internal/hook/sessionend.go","/home/sergio/Projects/personal/capy/internal/hook/sessionstart.go","/home/sergio/Projects/personal/capy/internal/hook/hook.go","/home/sergio/Projects/personal/capy/internal/store/entity.go"],"working_directory_absolute_path":"/home/sergio/Projects/personal/capy"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":424,"cache_read_input_tokens":25741,"output_tokens":1064,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":424,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaM9PEkstcVCXDfuLtwxq","type":"assistant","uuid":"7107feda-808e-46f5-945e-bdf9945ae635","timestamp":"2026-04-23T18:05:18.015Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"7107feda-808e-46f5-945e-bdf9945ae635","isSidechain":false,"promptId":"146d12f0-3fdd-4c52-b4e4-ddd71e37819a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JT1r4shhzYJr2xURdqGUEt","type":"tool_result","content":[{"type":"text","text":"{\"status\":\"continuation_available\",\"content\":\"This is a high-impact feature. Indexing conversational context solves a major pain point with ephemeral CLI sessions. Your instincts on the challenges (chunking, filtering, and dedup) are spot on. \\n\\nHere is my assessment of your questions, grounded in the current `capy` architecture.\\n\\n### A. Chunking Strategy\\n**Recommendation: Sliding window of turns (e.g., 4 turn pairs with a 1-pair overlap).**\\nIndividual turns lack context, and whole sessions dilute BM25 term frequencies. Topic-based segmentation requires LLM overhead, which violates our constraint of keeping this lightweight and automatic.\\n\\n*   **Implementation:** Do not use the existing `chunkJSON` (`internal/store/index.go`, line 184) because it will index the JSON AST structure. Instead, parse the JSONL into a plain text \\\"transcript\\\" format (e.g., `Human: ... \\\\n Assistant: ...`) and create a new `chunkTranscript` function.\\n*   **Why it fits:** This aligns perfectly with your existing `chunkPlainText` logic (`internal/store/chunk.go`, line 199) which already uses a fixed-line group with overlap. You can adapt that logic to split on turn boundaries instead of arbitrary lines.\\n\\n### B. Filtering Heuristics\\n**Recommendation: Strict exclusion to protect the BM25 index from noise.**\\n1.  **Turn Count:** Require at least 2 full turn pairs (Human + Assistant).\\n2.  **Command Filter:** Skip human messages that start with `/` (e.g., `/config`, `/compact`).\\n3.  **Content Extraction:** Extract *only* `type: \\\"text\\\"` from the message content arrays. Completely drop `tool_use` and `tool_result` blocks from the chunk body, as raw JSON/file dumps will destroy your IDF scores in `search.go`.\\n4.  **Length Threshold:** Skip sessions where the total extracted assistant text is under ~200 characters.\\n\\n### C. Structured Metadata\\n**Recommendation: Leverage the `Title` field for BM25 boosting.**\\nIn `internal/store/search.go` (line 246), you have a title-match boost. You should exploit this:\\n*   **Label:** Use the session ID or filename (e.g., `session_01H...`).\\n*   **Chunk Title:** Format as `Session <Date> | Turns <Start>-<End>`.\\n*   **Tool Context (Crucial):** Even though we drop tool *outputs*, we should extract the *names* of the tools used in that window and append them to the chunk `Title` or top of the `Content` (e.g., `Tools used: Bash, Replace`). This allows users to search \\\"when did we use the replace tool for X\\\".\\n*   **ContentType:** Introduce a new `\\\"session\\\"` content type in `internal/store/types.go` (line 23) and `index.go` (line 157).\\n\\n### D. Dedup and Incremental Indexing\\n**Recommendation: Rely on the existing `content_hash` mechanism.**\\nYou don't need a separate tracking table. `capy` already handles this elegantly in `internal/store/index.go` (line 66):\\n```go\\nerr = tx.Stmt(s.stmtFindSourceByLabel).QueryRow(label).Scan(&existingID, &existingHash, &existingKind)\\n```\\n1.  Use the session filename as the `label`.\\n2.  Hash the *filtered transcript* (not the raw JSONL) as the `content_hash`.\\n3.  Call `s.Index()`. If the session was appended to, the hash changes, and `capy` automatically deletes the old source and re-indexes the new one (line 95). If it hasn't changed, it returns `AlreadyIndexed: true` (line 92).\\n\\n### E. Session File Format\\nClaude Code JSONL typically follows the Anthropic API message structure. You'll need to parse each line as a JSON object:\\n*   `role`: `\\\"user\\\"` or `\\\"assistant\\\"`\\n*   `content`: Can be a string or an array of objects.\\n*   If array, look for `{\\\"type\\\": \\\"text\\\", \\\"text\\\": \\\"...\\\"}`.\\n*   Ignore `{\\\"type\\\": \\\"tool_use\\\"}` and `{\\\"type\\\": \\\"tool_result\\\"}`, but extract the `name` field from `tool_use` to enrich the chunk metadata as suggested in C.\\n\\n### F. Gotchas and Design Risks\\n\\n1.  **The DB Lock / Lifecycle Risk (CRITICAL):**\\n    Look at `internal/hook/sessionend.go` (lines 5-8):\\n    > *WAL checkpointing is NOT done here — the MCP server's own Close() handles that... Opening a second DB connection from the hook while the server is still running prevents SQLite from getting exclusive WAL access...*\\n    \\n    If the `sessionend` hook runs as a separate process and opens a DB connection to call `s.Index()`, it will compete with the shutting-down MCP server. While SQLite WAL allows concurrent writers, if the MCP server is trying to close and checkpoint, the hook might block it or hit a `SQLITE_BUSY` timeout.\\n    *Mitigation:* Ensure the hook uses `beginImmediate` (like you do in `cleanup.go`, line 246) to handle busy backoffs gracefully, and accept that indexing might occasionally fail if the lock is held too long.\\n\\n2.  **Retention Scoring Imbalance:**\\n    In `internal/store/cleanup.go` (line 24), `retentionScore` heavily favors code (`0.7`) over prose (`0.5`). Sessions will be classified as prose. If you index them as `KindDurable`, they might get evicted too quickly if not accessed.\\n    *Mitigation:* You may want to introduce a `KindSession` in `types.go` (line 8) with its own retention logic, or artificially boost the base salience of `ContentType == \\\"session\\\"` in `cleanup.go`.\\n\\n3.  **Hook Execution Time:**\\n    The `sessionend` hook is synchronous from Claude Code's perspective. If parsing a massive JSONL file takes 5 seconds, it will degrade the user experience when closing the app.\\n    *Mitigation:* The hook should read the file, but the actual parsing and indexing should ideally be fired off in a detached goroutine, or you should enforce a strict timeout on the indexing operation.\\n\\nPlease respond using the continuation_id from this response - your input is needed to proceed. Let me know which of these areas you'd like to drill into first, particularly how you want to handle the DB concurrency risk in the hook.\\n\\n---\\n\\nAGENT'S TURN: Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand.\",\"content_type\":\"text\",\"metadata\":{\"tool_name\":\"chat\",\"conversation_ready\":true,\"model_used\":\"gemini-3.1-pro-preview\",\"provider_used\":\"google\"},\"continuation_offer\":{\"continuation_id\":\"02160141-215e-4d68-9a4c-85d6bd844b4b\",\"note\":\"You can continue this conversation for 49 more exchanges.\",\"remaining_turns\":49}}"}]}]},"uuid":"6e57b5d9-d5f2-4192-a84c-024396b3e4c0","timestamp":"2026-04-23T18:05:54.992Z","toolUseResult":[{"type":"text","text":"{\"status\":\"continuation_available\",\"content\":\"This is a high-impact feature. Indexing conversational context solves a major pain point with ephemeral CLI sessions. Your instincts on the challenges (chunking, filtering, and dedup) are spot on. \\n\\nHere is my assessment of your questions, grounded in the current `capy` architecture.\\n\\n### A. Chunking Strategy\\n**Recommendation: Sliding window of turns (e.g., 4 turn pairs with a 1-pair overlap).**\\nIndividual turns lack context, and whole sessions dilute BM25 term frequencies. Topic-based segmentation requires LLM overhead, which violates our constraint of keeping this lightweight and automatic.\\n\\n*   **Implementation:** Do not use the existing `chunkJSON` (`internal/store/index.go`, line 184) because it will index the JSON AST structure. Instead, parse the JSONL into a plain text \\\"transcript\\\" format (e.g., `Human: ... \\\\n Assistant: ...`) and create a new `chunkTranscript` function.\\n*   **Why it fits:** This aligns perfectly with your existing `chunkPlainText` logic (`internal/store/chunk.go`, line 199) which already uses a fixed-line group with overlap. You can adapt that logic to split on turn boundaries instead of arbitrary lines.\\n\\n### B. Filtering Heuristics\\n**Recommendation: Strict exclusion to protect the BM25 index from noise.**\\n1.  **Turn Count:** Require at least 2 full turn pairs (Human + Assistant).\\n2.  **Command Filter:** Skip human messages that start with `/` (e.g., `/config`, `/compact`).\\n3.  **Content Extraction:** Extract *only* `type: \\\"text\\\"` from the message content arrays. Completely drop `tool_use` and `tool_result` blocks from the chunk body, as raw JSON/file dumps will destroy your IDF scores in `search.go`.\\n4.  **Length Threshold:** Skip sessions where the total extracted assistant text is under ~200 characters.\\n\\n### C. Structured Metadata\\n**Recommendation: Leverage the `Title` field for BM25 boosting.**\\nIn `internal/store/search.go` (line 246), you have a title-match boost. You should exploit this:\\n*   **Label:** Use the session ID or filename (e.g., `session_01H...`).\\n*   **Chunk Title:** Format as `Session <Date> | Turns <Start>-<End>`.\\n*   **Tool Context (Crucial):** Even though we drop tool *outputs*, we should extract the *names* of the tools used in that window and append them to the chunk `Title` or top of the `Content` (e.g., `Tools used: Bash, Replace`). This allows users to search \\\"when did we use the replace tool for X\\\".\\n*   **ContentType:** Introduce a new `\\\"session\\\"` content type in `internal/store/types.go` (line 23) and `index.go` (line 157).\\n\\n### D. Dedup and Incremental Indexing\\n**Recommendation: Rely on the existing `content_hash` mechanism.**\\nYou don't need a separate tracking table. `capy` already handles this elegantly in `internal/store/index.go` (line 66):\\n```go\\nerr = tx.Stmt(s.stmtFindSourceByLabel).QueryRow(label).Scan(&existingID, &existingHash, &existingKind)\\n```\\n1.  Use the session filename as the `label`.\\n2.  Hash the *filtered transcript* (not the raw JSONL) as the `content_hash`.\\n3.  Call `s.Index()`. If the session was appended to, the hash changes, and `capy` automatically deletes the old source and re-indexes the new one (line 95). If it hasn't changed, it returns `AlreadyIndexed: true` (line 92).\\n\\n### E. Session File Format\\nClaude Code JSONL typically follows the Anthropic API message structure. You'll need to parse each line as a JSON object:\\n*   `role`: `\\\"user\\\"` or `\\\"assistant\\\"`\\n*   `content`: Can be a string or an array of objects.\\n*   If array, look for `{\\\"type\\\": \\\"text\\\", \\\"text\\\": \\\"...\\\"}`.\\n*   Ignore `{\\\"type\\\": \\\"tool_use\\\"}` and `{\\\"type\\\": \\\"tool_result\\\"}`, but extract the `name` field from `tool_use` to enrich the chunk metadata as suggested in C.\\n\\n### F. Gotchas and Design Risks\\n\\n1.  **The DB Lock / Lifecycle Risk (CRITICAL):**\\n    Look at `internal/hook/sessionend.go` (lines 5-8):\\n    > *WAL checkpointing is NOT done here — the MCP server's own Close() handles that... Opening a second DB connection from the hook while the server is still running prevents SQLite from getting exclusive WAL access...*\\n    \\n    If the `sessionend` hook runs as a separate process and opens a DB connection to call `s.Index()`, it will compete with the shutting-down MCP server. While SQLite WAL allows concurrent writers, if the MCP server is trying to close and checkpoint, the hook might block it or hit a `SQLITE_BUSY` timeout.\\n    *Mitigation:* Ensure the hook uses `beginImmediate` (like you do in `cleanup.go`, line 246) to handle busy backoffs gracefully, and accept that indexing might occasionally fail if the lock is held too long.\\n\\n2.  **Retention Scoring Imbalance:**\\n    In `internal/store/cleanup.go` (line 24), `retentionScore` heavily favors code (`0.7`) over prose (`0.5`). Sessions will be classified as prose. If you index them as `KindDurable`, they might get evicted too quickly if not accessed.\\n    *Mitigation:* You may want to introduce a `KindSession` in `types.go` (line 8) with its own retention logic, or artificially boost the base salience of `ContentType == \\\"session\\\"` in `cleanup.go`.\\n\\n3.  **Hook Execution Time:**\\n    The `sessionend` hook is synchronous from Claude Code's perspective. If parsing a massive JSONL file takes 5 seconds, it will degrade the user experience when closing the app.\\n    *Mitigation:* The hook should read the file, but the actual parsing and indexing should ideally be fired off in a detached goroutine, or you should enforce a strict timeout on the indexing operation.\\n\\nPlease respond using the continuation_id from this response - your input is needed to proceed. Let me know which of these areas you'd like to drill into first, particularly how you want to handle the DB concurrency risk in the hook.\\n\\n---\\n\\nAGENT'S TURN: Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand.\",\"content_type\":\"text\",\"metadata\":{\"tool_name\":\"chat\",\"conversation_ready\":true,\"model_used\":\"gemini-3.1-pro-preview\",\"provider_used\":\"google\"},\"continuation_offer\":{\"continuation_id\":\"02160141-215e-4d68-9a4c-85d6bd844b4b\",\"note\":\"You can continue this conversation for 49 more exchanges.\",\"remaining_turns\":49}}"}],"sourceToolAssistantUUID":"7107feda-808e-46f5-945e-bdf9945ae635","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"type":"last-prompt","lastPrompt":"1. Format - yes, only the human/assistant conversations. Skip raw tool results, file edits (I guess they're part of tool results). Also need to take care of sessions that didn't have any meaningful in…","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
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 {"parentUuid":"041eed66-4f43-4a7d-b325-3bdbbf4278db","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Vsmug9YHqyqNxJgKz69Twc","type":"message","role":"assistant","content":[{"type":"text","text":"Good analysis from PAL. Here's my synthesis — where I agree, where I'd push back, and the open decisions.\n\n**Chunking — agree with sliding window, but details matter.** 4 turn pairs with 1-pair overlap is a reasonable starting point. Converting to transcript format (`Human: ...\\nAssistant: ...`) before chunking makes sense — reuses `chunkPlainText` logic rather than inventing something new. The key insight: split on turn boundaries, not arbitrary line counts.\n\n**Filtering — mostly agree, one correction.** The `/` command filter should be per-message, not per-session. Someone might `/config` then have a real conversation. The session-level gate should be: minimum 2 meaningful turn pairs AND minimum ~200 chars of assistant text. That catches the \"opened and closed\" sessions cleanly.\n\n**Metadata — the tool-name extraction is a genuinely good idea.** Even without tool outputs, knowing \"we used Bash and Edit here\" makes chunks findable for queries like \"when did we set up the CI pipeline.\" Storing tool names in the chunk title or as a prefix exploits the existing BM25 title boost in search.\n\n**Dedup — clean, use existing content_hash.** No new tracking table. Session filename as label, hash of the filtered transcript as content_hash. Re-indexes automatically if the session grew (Claude Code can append to sessions on resume).\n\n**The three gotchas PAL flagged are all real:**\n\n1. **DB lock contention** — this is the biggest risk. The session-end hook runs while the MCP server may still be shutting down. We need to either: (a) ensure the hook uses `beginImmediate` with proper busy backoff, or (b) defer indexing to next session start instead.\n\n2. **Retention** — PAL is right that sessions would get classified as prose and evicted. We need either a new `KindSession` with its own retention rules, or just set a significantly higher base TTL for session-sourced chunks. Given your requirement for \"progress over time,\" I'd lean toward a dedicated kind.\n\n3. **Hook latency** — parsing a large JSONL file synchronously at session end would be noticeable. The hook should fork the actual work into a background process (or we index at next session *start* instead, which sidesteps both this and the DB lock issue).\n\n**My strongest opinion: index at session start, not session end.** It solves two problems at once — no DB lock contention with the dying server, and no UX penalty when closing. The trade-off is a one-session delay before content becomes searchable, which seems fine since you'd never search the *current* session anyway.\n\nWhat do you think — session-start indexing, or do you want to solve the session-end concurrency?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2989,"cache_read_input_tokens":26165,"output_tokens":1375,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2989,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaM9TZjzaUoUVEyKZgNqz","type":"assistant","uuid":"584e176d-9d83-4a07-bed1-9836d797470a","timestamp":"2026-04-23T18:06:28.003Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"1e4326ec-1599-462b-8829-bbf2a27a373b","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01ET2USKsfvSBcGBoF74Fpkf","type":"message","role":"assistant","content":[{"type":"text","text":"You're right, you explicitly said \"separate `session` source kind\" in the issue — I should have picked that up instead of treating it as an open question. A new `KindSession` with its own retention rules, settled.\n\nFor the dedup question — you don't need to know *which* session just ended. You do a sweep:\n\n1. Session-start hook fires for the new session\n2. Scan all session files in `~/.claude/projects/<project-hash>/`\n3. For each file, use the filename as the `label` and pass it through `Index()`\n4. The existing `content_hash` check in `Index()` handles the rest — if the hash matches, it returns `AlreadyIndexed: true` and moves on. If the file grew (resumed session), the hash differs and it re-indexes.\n5. The just-started session is either empty or has one turn — gets filtered out by the minimum turn count heuristic\n\nThe concern is performance: parsing every JSONL file on every session start just to compute hashes gets expensive with hundreds of sessions. Two options:\n\n**A. Mtime gate** — before parsing a file, compare its mtime against the `indexed_at` timestamp on the stored source. If the file hasn't been modified since we last indexed it, skip entirely. No parsing, no hashing. Only new or modified files get processed.\n\n**B. Watermark file** — write a simple timestamp file (e.g. `.capy_session_indexed_at`) after each sweep. On next sweep, only look at files with mtime newer than the watermark. Even cheaper than checking per-file against the DB.\n\nI'd lean toward **A** since it uses the existing source metadata and handles the edge case where a session file was modified but the source record was cleaned up for some other reason. B is simpler but slightly more fragile.\n\nEither way the steady-state cost is: one `stat()` per session file + full parse only for the one session that actually ended. That's negligible.\n\nDoes this address your concern, or do you see a hole in the sweep approach?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1443,"cache_read_input_tokens":29154,"output_tokens":1308,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1443,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaM9uctEWzgMu8TiACees","type":"assistant","uuid":"c58c710c-13d0-49b8-90bc-eac66d8fea4a","timestamp":"2026-04-23T18:12:22.666Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"4961e0f5-19b4-47d6-97cf-9c34707a3082","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01A5UXvZu62s5FJWwPGWUGK5","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01TBmrvSQNyCYrZnmFANtYa8","name":"mcp__pal__chat","input":{"prompt":"Continuing our sessionflow RAG discussion. We've made several decisions and I want your feedback on the refined approach.\n\n**Decisions made:**\n\n1. **New `KindSession`** — sessions get their own source kind with dedicated retention rules. Longer TTL than regular content since sessions represent \"progress over time.\"\n\n2. **Indexing at session START, not session END.** This sidesteps two problems:\n   - No DB lock contention with the dying MCP server\n   - No UX penalty when closing a session\n   - Trade-off: one-session delay before content is searchable (acceptable — you never search the current session)\n\n3. **Sweep-based dedup approach:**\n   - On session-start hook, scan ALL session files in `~/.claude/projects/<project-hash>/`\n   - Use session filename as `label`, pass through existing `Index()`\n   - Existing `content_hash` check handles dedup — `AlreadyIndexed: true` if unchanged\n   - The just-started session gets filtered out by minimum turn count (< 2 meaningful turn pairs)\n   - **Mtime gate optimization:** Before parsing a file, compare its mtime against `indexed_at` on the stored source record. Skip files that haven't been modified. Steady-state cost: one `stat()` per session file, full parse only for the newly-ended session.\n\n4. **Chunking:** Sliding window of ~4 turn pairs with 1-pair overlap, converted to transcript format before chunking.\n\n5. **Filtering:** Per-message `/` command filter (not per-session). Session-level gate: min 2 meaningful turn pairs AND min ~200 chars assistant text.\n\n6. **Metadata:** Tool names extracted from `tool_use` blocks and included in chunk title/prefix for BM25 boost.\n\n**Open questions I want your take on:**\n\nA. **Session file discovery:** Claude Code stores sessions in `~/.claude/projects/`. The project path is hashed. How do we reliably find the right project directory from within the session-start hook? The hook receives context about the current session — do we get the project path from there, or do we need to discover it?\n\nB. **KindSession retention rules:** What should the concrete TTL be? Current cleanup uses a scoring system based on access patterns, content type, and age. For sessions, what's the right balance? Never expire? Expire after N months? Expire based on access frequency like everything else but with a much higher base score?\n\nC. **Resumed sessions:** Claude Code can resume sessions. When a session is resumed, the JSONL file grows. Our mtime gate catches this and re-indexes. But re-indexing means deleting all old chunks and creating new ones. For a large resumed session, this means re-chunking the entire transcript including parts that were already indexed. Is there a smarter incremental approach, or is the full re-index acceptable given it only happens on resume?\n\nD. **Session file format specifics:** I need to parse Claude Code JSONL reliably. Are there edge cases in the format? System messages, compact markers, image content blocks, multi-turn tool chains — what should we handle vs skip?\n\nE. **The hook implementation:** The session-start hook currently exists (`internal/hook/sessionstart.go`). The sweep + index operation could take a few seconds if there are many changed sessions. Should this be synchronous (blocks until done) or should the hook fork a background goroutine? If background, how do we handle the case where the user immediately searches for session content before indexing completes?\n\nF. **Content quality:** Should we do any light processing of assistant text before indexing? For example, stripping markdown formatting, code blocks (which are usually shown inline and may not be the assistant's \"reasoning\"), or keeping everything raw?\n\nGive me your honest assessment — poke holes in anything that seems fragile.","model":"gemini-3.1-pro-preview","thinking_mode":"high","temperature":0.4,"continuation_id":"02160141-215e-4d68-9a4c-85d6bd844b4b","absolute_file_paths":["/home/sergio/Projects/personal/capy/internal/hook/sessionstart.go","/home/sergio/Projects/personal/capy/internal/hook/sessionend.go","/home/sergio/Projects/personal/capy/internal/hook/hook.go","/home/sergio/Projects/personal/capy/internal/store/types.go","/home/sergio/Projects/personal/capy/internal/store/cleanup.go","/home/sergio/Projects/personal/capy/internal/store/index.go","/home/sergio/Projects/personal/capy/internal/config/paths.go"],"working_directory_absolute_path":"/home/sergio/Projects/personal/capy"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1338,"cache_read_input_tokens":30597,"output_tokens":1281,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1338,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMA5hSqxjduWEWmhTQqU","type":"assistant","uuid":"8fc43142-6bf1-4836-8f7e-4adbd06d392d","timestamp":"2026-04-23T18:14:31.209Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"8fc43142-6bf1-4836-8f7e-4adbd06d392d","isSidechain":false,"promptId":"e9806bb1-ecb2-46dd-ad57-37f8f4d016fa","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TBmrvSQNyCYrZnmFANtYa8","type":"tool_result","content":[{"type":"text","text":"{\"status\":\"continuation_available\",\"content\":\"This is a very solid, pragmatic design. You've correctly identified the major bottlenecks, especially moving ingestion to session START to avoid the WAL lock contention during teardown. \\n\\nHere is my assessment of your open questions, including a critical architectural catch regarding how hooks execute.\\n\\n### A. Session file discovery\\n**You already have the exact tools for this.** \\nIn `internal/hook/hook.go`, the `Run` function signature already receives `projectDir string` (line 13). You don't need to discover it from Claude Code's internal state. \\nYou can simply pass this `projectDir` to your existing `ProjectHash` function in `internal/config/paths.go` (line 42):\\n```go\\nhash := config.ProjectHash(projectDir)\\nsessionDir := filepath.Join(os.Getenv(\\\"HOME\\\"), \\\".claude\\\", \\\"projects\\\", hash)\\n```\\nThis guarantees you are looking at the exact session history for the current workspace.\\n\\n### B. KindSession retention rules\\n**Recommendation: Use a strict TTL, bypassing the durable retention math.**\\nIf you look at `internal/store/cleanup.go`, `retentionScore` (line 22) is highly tuned for code/prose salience and access frequency. Sessions are historical context; their value decays strictly with time, not necessarily with access frequency. \\nTreat `KindSession` similarly to `KindEphemeral` but with a much longer window (e.g., 30 or 60 days). You can adapt `cleanupEphemeral` (`internal/store/cleanup.go`, line 154) to accept a map of kinds to TTLs, allowing you to purge 24h ephemeral scratchpad data and 30-day session data in the same sweep without polluting the `KindDurable` scoring logic.\\n\\n### C. Resumed sessions\\n**Recommendation: Full re-index. Do not build an incremental updater.**\\nBuilding an incremental chunk updater for a JSONL file is a classic over-engineering trap. SQLite handles deletes and inserts incredibly fast. Your existing `deleteSourceTx` (`internal/store/index.go`, line 174) followed by the chunk inserts is already wrapped in a single transaction. \\nGiven that the mtime gate prevents this from running on unchanged files, a full re-index of a resumed session (which might be a few megabytes at most) will take milliseconds. Keep it simple and idempotent.\\n\\n### D. Session file format specifics\\n**Recommendation: Keep it simple, but don't drop compact markers.**\\n*   **System messages:** Skip them. They are static boilerplate.\\n*   **Image blocks:** Skip them.\\n*   **Tool chains:** As agreed, extract the `name` from `tool_use` for metadata, but drop the `tool_result` content.\\n*   **Compact markers:** Claude Code occasionally summarizes the conversation to save context window. *Keep these.* They are dense, high-signal representations of the project state and are excellent for BM25. Treat them as assistant text.\\n\\n### E. The hook implementation (CRITICAL RISK)\\n**Recommendation: Do NOT do this in the hook. Move it to MCP server startup.**\\nThere is a fundamental lifecycle issue here. The `sessionstart` hook (`internal/hook/hook.go`) is a short-lived process invoked by Claude Code. \\n1. If you run the sweep synchronously, you block Claude Code's startup sequence. \\n2. If you fork a goroutine inside the hook, it will be immediately killed when the hook process writes to stdout and exits.\\n\\nInstead, shift the ingestion trigger to the **MCP server initialization**. When Claude Code starts a session, it boots your MCP server as a persistent process. Have the MCP server fire off a detached goroutine on startup to run the sweep. \\n*   It has safe, long-lived access to the DB.\\n*   It doesn't block Claude Code's UI.\\n*   The 1-2 second delay before the previous session becomes searchable is completely invisible to the user, as they are just starting their prompt.\\n\\n### F. Content quality\\n**Recommendation: Keep it raw.**\\nDo not strip markdown or code blocks. FTS5 tokenizers (like `porter unicode61` in your schema, `internal/store/schema.go`, line 26) already strip punctuation and normalize text. More importantly, the code blocks the assistant generates are often the actual \\\"answers\\\" or \\\"decisions\\\" you'll be searching for later. Stripping them removes the highest-value payload of the session. Your existing `chunkPlainText` logic will handle the raw text perfectly well.\\n\\n***\\n\\nThe shift to MCP server startup rather than the `sessionstart` hook is the biggest architectural pivot here, but it simplifies the concurrency model immensely. \\n\\nPlease respond using the continuation_id from this response - your input is needed to proceed. Let me know if you agree with moving the trigger to the MCP server boot sequence, and we can start mapping out the `chunkTranscript` implementation.\\n\\n---\\n\\nAGENT'S TURN: Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand.\",\"content_type\":\"text\",\"metadata\":{\"tool_name\":\"chat\",\"conversation_ready\":true,\"model_used\":\"gemini-3.1-pro-preview\",\"provider_used\":\"google\"},\"continuation_offer\":{\"continuation_id\":\"02160141-215e-4d68-9a4c-85d6bd844b4b\",\"note\":\"You can continue this conversation for 44 more exchanges.\",\"remaining_turns\":44}}"}]}]},"uuid":"31b82d0d-9cfb-4aad-bc86-adb3a6ee073e","timestamp":"2026-04-23T18:15:04.206Z","toolUseResult":[{"type":"text","text":"{\"status\":\"continuation_available\",\"content\":\"This is a very solid, pragmatic design. You've correctly identified the major bottlenecks, especially moving ingestion to session START to avoid the WAL lock contention during teardown. \\n\\nHere is my assessment of your open questions, including a critical architectural catch regarding how hooks execute.\\n\\n### A. Session file discovery\\n**You already have the exact tools for this.** \\nIn `internal/hook/hook.go`, the `Run` function signature already receives `projectDir string` (line 13). You don't need to discover it from Claude Code's internal state. \\nYou can simply pass this `projectDir` to your existing `ProjectHash` function in `internal/config/paths.go` (line 42):\\n```go\\nhash := config.ProjectHash(projectDir)\\nsessionDir := filepath.Join(os.Getenv(\\\"HOME\\\"), \\\".claude\\\", \\\"projects\\\", hash)\\n```\\nThis guarantees you are looking at the exact session history for the current workspace.\\n\\n### B. KindSession retention rules\\n**Recommendation: Use a strict TTL, bypassing the durable retention math.**\\nIf you look at `internal/store/cleanup.go`, `retentionScore` (line 22) is highly tuned for code/prose salience and access frequency. Sessions are historical context; their value decays strictly with time, not necessarily with access frequency. \\nTreat `KindSession` similarly to `KindEphemeral` but with a much longer window (e.g., 30 or 60 days). You can adapt `cleanupEphemeral` (`internal/store/cleanup.go`, line 154) to accept a map of kinds to TTLs, allowing you to purge 24h ephemeral scratchpad data and 30-day session data in the same sweep without polluting the `KindDurable` scoring logic.\\n\\n### C. Resumed sessions\\n**Recommendation: Full re-index. Do not build an incremental updater.**\\nBuilding an incremental chunk updater for a JSONL file is a classic over-engineering trap. SQLite handles deletes and inserts incredibly fast. Your existing `deleteSourceTx` (`internal/store/index.go`, line 174) followed by the chunk inserts is already wrapped in a single transaction. \\nGiven that the mtime gate prevents this from running on unchanged files, a full re-index of a resumed session (which might be a few megabytes at most) will take milliseconds. Keep it simple and idempotent.\\n\\n### D. Session file format specifics\\n**Recommendation: Keep it simple, but don't drop compact markers.**\\n*   **System messages:** Skip them. They are static boilerplate.\\n*   **Image blocks:** Skip them.\\n*   **Tool chains:** As agreed, extract the `name` from `tool_use` for metadata, but drop the `tool_result` content.\\n*   **Compact markers:** Claude Code occasionally summarizes the conversation to save context window. *Keep these.* They are dense, high-signal representations of the project state and are excellent for BM25. Treat them as assistant text.\\n\\n### E. The hook implementation (CRITICAL RISK)\\n**Recommendation: Do NOT do this in the hook. Move it to MCP server startup.**\\nThere is a fundamental lifecycle issue here. The `sessionstart` hook (`internal/hook/hook.go`) is a short-lived process invoked by Claude Code. \\n1. If you run the sweep synchronously, you block Claude Code's startup sequence. \\n2. If you fork a goroutine inside the hook, it will be immediately killed when the hook process writes to stdout and exits.\\n\\nInstead, shift the ingestion trigger to the **MCP server initialization**. When Claude Code starts a session, it boots your MCP server as a persistent process. Have the MCP server fire off a detached goroutine on startup to run the sweep. \\n*   It has safe, long-lived access to the DB.\\n*   It doesn't block Claude Code's UI.\\n*   The 1-2 second delay before the previous session becomes searchable is completely invisible to the user, as they are just starting their prompt.\\n\\n### F. Content quality\\n**Recommendation: Keep it raw.**\\nDo not strip markdown or code blocks. FTS5 tokenizers (like `porter unicode61` in your schema, `internal/store/schema.go`, line 26) already strip punctuation and normalize text. More importantly, the code blocks the assistant generates are often the actual \\\"answers\\\" or \\\"decisions\\\" you'll be searching for later. Stripping them removes the highest-value payload of the session. Your existing `chunkPlainText` logic will handle the raw text perfectly well.\\n\\n***\\n\\nThe shift to MCP server startup rather than the `sessionstart` hook is the biggest architectural pivot here, but it simplifies the concurrency model immensely. \\n\\nPlease respond using the continuation_id from this response - your input is needed to proceed. Let me know if you agree with moving the trigger to the MCP server boot sequence, and we can start mapping out the `chunkTranscript` implementation.\\n\\n---\\n\\nAGENT'S TURN: Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand.\",\"content_type\":\"text\",\"metadata\":{\"tool_name\":\"chat\",\"conversation_ready\":true,\"model_used\":\"gemini-3.1-pro-preview\",\"provider_used\":\"google\"},\"continuation_offer\":{\"continuation_id\":\"02160141-215e-4d68-9a4c-85d6bd844b4b\",\"note\":\"You can continue this conversation for 44 more exchanges.\",\"remaining_turns\":44}}"}],"sourceToolAssistantUUID":"8fc43142-6bf1-4836-8f7e-4adbd06d392d","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"last-prompt","lastPrompt":"sounds good  continue the pal chat to further converse and corroborate the idea and concerns","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
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 {"parentUuid":"31b82d0d-9cfb-4aad-bc86-adb3a6ee073e","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_015XeeokTz4NUA9RYz2ndB7E","type":"message","role":"assistant","content":[{"type":"text","text":"PAL came back with some sharp corrections. Here's the important stuff:\n\n**Session discovery — solved.** The hook already receives `projectDir`. Use the existing `ProjectHash` in `config/paths.go` to derive the sessions directory. No discovery needed.\n\n**Retention — time-based TTL, not scoring.** PAL argues sessions decay with time, not access frequency. Suggests treating `KindSession` like `KindEphemeral` but with 30-60 day TTL — adapt `cleanupEphemeral` to accept per-kind TTLs. I think this is right. The existing `retentionScore` math is tuned for code/prose salience and would mistreat sessions.\n\n**Resumed sessions — full re-index, no incremental.** Agreed. `deleteSourceTx` + re-insert in one transaction is milliseconds. Building an incremental chunk updater for this is over-engineering.\n\n**Compact markers — keep them.** When Claude Code compacts a conversation, the summary is dense, high-signal text. Good for BM25. Treat as assistant text. I agree with this — compaction summaries are arguably *more* searchable than the raw conversation.\n\n**Content — keep raw, don't strip markdown.** FTS5 porter tokenizer already normalizes. Code blocks in assistant responses are often the actual decisions/answers. Stripping them removes the highest-value content.\n\n**The big one — E. Don't index in the hook. Index at MCP server startup.**\n\nPAL caught a real lifecycle problem I missed: the session-start hook is a short-lived process. If you fork a goroutine inside it, it dies when the hook exits. Synchronous indexing blocks Claude Code's startup. \n\nThe fix: trigger the sweep in the MCP server's `init` sequence instead. The MCP server is a long-lived process that Claude Code boots at session start. A background goroutine there has safe DB access, doesn't block the UI, and the 1-2 second delay is invisible since the user is just starting to type.\n\nThis is a better answer than what I proposed. The hook can still be the *trigger* (it already boots the server), but the actual indexing logic lives in the server lifecycle, not the hook.\n\nWhat's your read on these? Particularly the MCP server startup vs hook question — it changes where the code lives."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":2647,"cache_read_input_tokens":31935,"output_tokens":539,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2647,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMAA3marTXdrCMKHbupi","type":"assistant","uuid":"0afd9fb7-88e1-4403-a03e-a45c32fb0cc6","timestamp":"2026-04-23T18:15:17.681Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"74a49a23-9668-470f-ae00-712728b279b3","isSidechain":false,"type":"system","subtype":"away_summary","content":"We're designing sessionflow RAG (issue #24) to make past Claude Code sessions searchable via FTS5. We finished the design discussion with PAL and converged on key decisions. Next step is getting your sign-off on triggering indexing at MCP server startup instead of in the hook. (disable recaps in /config)","timestamp":"2026-04-23T18:18:22.002Z","uuid":"31f36f96-f281-4ce7-b680-24aaac1aeefd","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"e336c3cf-1f94-4bc1-bbfc-fab4f9b10dfe","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_012agJaF4r9kNYvCJvP799Nj","type":"message","role":"assistant","content":[{"type":"text","text":"Good. The design is solid. Let me capture the final decisions:\n\n1. **New `KindSession`** — dedicated source kind, time-based TTL (30-60 days), bypasses durable retention scoring\n2. **Trigger: MCP server startup** — background goroutine in server init, not in the hook\n3. **Sweep approach** — scan all session files, mtime gate to skip unchanged, existing `content_hash` for dedup\n4. **Session discovery** — `projectDir` from hook context + `ProjectHash()` to find session directory\n5. **Chunking** — sliding window of ~4 turn pairs, 1-pair overlap, transcript format via adapted `chunkPlainText`\n6. **Filtering** — skip system messages, images, tool results; keep compact summaries; per-message `/` command filter; session gate: min 2 turn pairs + min ~200 chars assistant text\n7. **Metadata** — tool names extracted from `tool_use` blocks into chunk title for BM25 boost; `\"session\"` content type\n8. **Resumed sessions** — full re-index, no incremental\n9. **Content** — raw, no stripping\n\nWant to move to the design phase? I can run `kk:design` to produce the spec and task breakdown."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":544,"cache_read_input_tokens":34582,"output_tokens":424,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":544,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMAaX5KFvj5FxXoLDV9V","type":"assistant","uuid":"ff85be64-eee8-4675-a7f8-864b0baf6e4c","timestamp":"2026-04-23T18:20:46.016Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"bd9ab536-95ed-411b-8ab3-89b1a4cf7ccd","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_011LWD67DiETKZP9CqwTZs4w","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01U5DQxw6eFrL7XaieT12HrY","name":"Skill","input":{"skill":"kk:design","args":"Sessionflow RAG (GitHub issue #24) — index Claude Code session transcripts into capy's FTS5 knowledge base for on-demand historical search.\n\n## Context\n\ncapy is an MCP server / Claude Code plugin that indexes tool outputs into SQLite FTS5 with BM25 search. Sessions in `~/.claude/projects/<project-hash>/` contain valuable decisions and rationale that are lost after conversations end.\n\n## Finalized Design Decisions\n\n1. **New `KindSession`** — dedicated source kind with time-based TTL (30-60 days), bypasses the durable retention scoring system entirely. Adapt `cleanupEphemeral` to accept per-kind TTLs.\n\n2. **Trigger: MCP server startup** — NOT in hooks. The MCP server fires a background goroutine on startup to run the session sweep. The hook is short-lived and can't sustain background work. The server is long-lived, has safe DB access, doesn't block Claude Code UI.\n\n3. **Sweep-based dedup:**\n   - On server startup, scan ALL session JSONL files in `~/.claude/projects/<project-hash>/`\n   - Session discovery: use `projectDir` (available from hook context) + existing `ProjectHash()` in `config/paths.go`\n   - Use session filename as `label`, pass through existing `Index()`\n   - Mtime gate: compare file mtime against `indexed_at` on stored source record. Skip unchanged files.\n   - Existing `content_hash` handles dedup — returns `AlreadyIndexed: true` if hash unchanged\n   - Resumed sessions: full re-index (delete + re-insert in one tx), no incremental updater\n\n4. **Chunking:** Sliding window of ~4 turn pairs with 1-pair overlap. Convert JSONL to transcript format (`Human: ...\\nAssistant: ...`) then chunk. Adapt existing `chunkPlainText` logic to split on turn boundaries.\n\n5. **Filtering (per-message):**\n   - Skip system messages, image content blocks, tool_result content\n   - Skip human messages starting with `/` (commands like /config, /help)\n   - Keep compact summaries (dense, high-signal assistant text)\n   - Extract only `type: \"text\"` from content arrays\n   - Session-level gate: minimum 2 meaningful turn pairs AND minimum ~200 chars total assistant text\n\n6. **Metadata:**\n   - New `\"session\"` content type in types.go\n   - Tool names extracted from `tool_use` blocks included in chunk title/prefix for BM25 title boost\n   - Chunk title format: `Session <Date> | Turns <Start>-<End> | Tools: <names>`\n   - Source label: session filename\n\n7. **Content processing:** Keep raw — no markdown stripping, no code block removal. FTS5 porter tokenizer handles normalization. Code blocks in assistant responses are often the actual answers/decisions.\n\n8. **NOT exposed as MCP tool** — entirely automatic, the assistant never needs to think about this.\n\n## Key Files to Understand\n\n- `internal/store/types.go` — source kinds, content types\n- `internal/store/index.go` — Index() function, content_hash dedup, deleteSourceTx\n- `internal/store/cleanup.go` — retention scoring, cleanupEphemeral\n- `internal/store/chunk.go` — chunkPlainText, chunking logic\n- `internal/store/schema.go` — FTS5 schema\n- `internal/hook/sessionstart.go` — session start hook\n- `internal/hook/hook.go` — hook infrastructure, Run() receives projectDir\n- `internal/config/paths.go` — ProjectHash(), path resolution\n- `internal/server/lifecycle.go` — MCP server init/shutdown\n- `internal/server/server.go` — server struct, startup sequence\n\n## References\n- GitHub issue: https://github.com/serpro69/capy/issues/24\n- Inspiration (not directly applicable): https://github.com/thedotmack/claude-mem"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":441,"cache_read_input_tokens":35126,"output_tokens":1064,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":441,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMAdT8Gg9cxnkN24Z2oY","type":"assistant","uuid":"f53e1d1c-c85c-40a1-be8a-7b646d7a0ec7","timestamp":"2026-04-23T18:21:36.474Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"f53e1d1c-c85c-40a1-be8a-7b646d7a0ec7","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"type":"tool_result","tool_use_id":"toolu_01U5DQxw6eFrL7XaieT12HrY","content":"Launching skill: kk:design"}]},"uuid":"b8e73347-a829-4fd2-9437-939005894854","timestamp":"2026-04-23T18:21:36.500Z","toolUseResult":{"success":true,"commandName":"kk:design"},"sourceToolAssistantUUID":"f53e1d1c-c85c-40a1-be8a-7b646d7a0ec7","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"b8e73347-a829-4fd2-9437-939005894854","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"type":"text","text":"Base directory for this skill: /home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/skills/design\n\n# Task Analysis Process\n\n**Goal: Before writing any code, make sure you understand the requirements and have an implementation plan ready.**\n\n## Conventions\n\nRead capy knowledge base conventions at [shared-capy-knowledge-protocol.md](shared-capy-knowledge-protocol.md).\n\nProfile detection is delegated to [shared-profile-detection.md](shared-profile-detection.md). When an active profile contributes a `design/` subdirectory (e.g., `/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/k8s/design/`), its `questions.md` feeds the idea-refinement question pool and its `sections.md` lists required sections the design document must cover. Both the idea-to-design and continue-WIP flows consult the shared procedure; see each flow's workflow file for the specific integration points.\n\n## Ideas and Prototypes\n\n_Use this for ideas that are not fully thought out and do not have a fully-formed design/specification and/or implementation-plan._\n\n**For example:** I've got an idea I want to talk through with you before we proceed with the implementation.\n\n**Your job:** Help me turn it into a fully formed design, spec, implementation plan, and task list.\n\nSee [idea-process.md](./idea-process.md).\n\n## Continue WIP Feature\n\n_Use this to resume work on a feature that already has design docs and a task list in `/docs/wip/`._\n\n**For example:** Let's continue working on the auth system.\n\n**Your job:** Review the current state of the feature, understand what's been done and what's next, then proceed with implementation.\n\nSee [existing-task-process.md](./existing-task-process.md).\n\n\nARGUMENTS: Sessionflow RAG (GitHub issue #24) — index Claude Code session transcripts into capy's FTS5 knowledge base for on-demand historical search.\n\n## Context\n\ncapy is an MCP server / Claude Code plugin that indexes tool outputs into SQLite FTS5 with BM25 search. Sessions in `~/.claude/projects/<project-hash>/` contain valuable decisions and rationale that are lost after conversations end.\n\n## Finalized Design Decisions\n\n1. **New `KindSession`** — dedicated source kind with time-based TTL (30-60 days), bypasses the durable retention scoring system entirely. Adapt `cleanupEphemeral` to accept per-kind TTLs.\n\n2. **Trigger: MCP server startup** — NOT in hooks. The MCP server fires a background goroutine on startup to run the session sweep. The hook is short-lived and can't sustain background work. The server is long-lived, has safe DB access, doesn't block Claude Code UI.\n\n3. **Sweep-based dedup:**\n   - On server startup, scan ALL session JSONL files in `~/.claude/projects/<project-hash>/`\n   - Session discovery: use `projectDir` (available from hook context) + existing `ProjectHash()` in `config/paths.go`\n   - Use session filename as `label`, pass through existing `Index()`\n   - Mtime gate: compare file mtime against `indexed_at` on stored source record. Skip unchanged files.\n   - Existing `content_hash` handles dedup — returns `AlreadyIndexed: true` if hash unchanged\n   - Resumed sessions: full re-index (delete + re-insert in one tx), no incremental updater\n\n4. **Chunking:** Sliding window of ~4 turn pairs with 1-pair overlap. Convert JSONL to transcript format (`Human: ...\\nAssistant: ...`) then chunk. Adapt existing `chunkPlainText` logic to split on turn boundaries.\n\n5. **Filtering (per-message):**\n   - Skip system messages, image content blocks, tool_result content\n   - Skip human messages starting with `/` (commands like /config, /help)\n   - Keep compact summaries (dense, high-signal assistant text)\n   - Extract only `type: \"text\"` from content arrays\n   - Session-level gate: minimum 2 meaningful turn pairs AND minimum ~200 chars total assistant text\n\n6. **Metadata:**\n   - New `\"session\"` content type in types.go\n   - Tool names extracted from `tool_use` blocks included in chunk title/prefix for BM25 title boost\n   - Chunk title format: `Session <Date> | Turns <Start>-<End> | Tools: <names>`\n   - Source label: session filename\n\n7. **Content processing:** Keep raw — no markdown stripping, no code block removal. FTS5 porter tokenizer handles normalization. Code blocks in assistant responses are often the actual answers/decisions.\n\n8. **NOT exposed as MCP tool** — entirely automatic, the assistant never needs to think about this.\n\n## Key Files to Understand\n\n- `internal/store/types.go` — source kinds, content types\n- `internal/store/index.go` — Index() function, content_hash dedup, deleteSourceTx\n- `internal/store/cleanup.go` — retention scoring, cleanupEphemeral\n- `internal/store/chunk.go` — chunkPlainText, chunking logic\n- `internal/store/schema.go` — FTS5 schema\n- `internal/hook/sessionstart.go` — session start hook\n- `internal/hook/hook.go` — hook infrastructure, Run() receives projectDir\n- `internal/config/paths.go` — ProjectHash(), path resolution\n- `internal/server/lifecycle.go` — MCP server init/shutdown\n- `internal/server/server.go` — server struct, startup sequence\n\n## References\n- GitHub issue: https://github.com/serpro69/capy/issues/24\n- Inspiration (not directly applicable): https://github.com/thedotmack/claude-mem"}]},"isMeta":true,"uuid":"19455157-c405-4bb5-afa3-c083e731953b","timestamp":"2026-04-23T18:21:36.499Z","sourceToolUseID":"toolu_01U5DQxw6eFrL7XaieT12HrY","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"e322c48a-aab8-428d-8b2c-f055e6bf472a","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012PkNnKnbtT3iT8qSnxBY6p","type":"tool_result","content":"1\t### Workflow\n2\t\n3\tCopy this checklist and check off items as you complete them:\n4\t\n5\t```\n6\tTask Progress:\n7\t- [ ] Step 1: Understand the current state of the project\n8\t- [ ] Step 2: Check the documentation\n9\t- [ ] Step 3: Help refine the idea/feature\n10\t- [ ] Step 4: Describe the design\n11\t- [ ] Step 5: Document the design\n12\t- [ ] Step 6: Create the task list\n13\t```\n14\t\n15\t**Step 1: Understand the current state of the project**\n16\t\n17\tTo properly refine the idea into a fully-formed design you need to **understand the existing code** in our working directory to know where we're starting off.\n18\t\n19\t**Step 2: Check the documentation**\n20\t\n21\tIn order to gain a better understanding of the project, **check the contributing guidelines and any relevant documentation**. For example, take a look at `CONTRIBUTING.md` and `docs` directory.\n22\t\n23\t**Capy search:** Before refining the idea, search `kk:arch-decisions` and `kk:project-conventions` for prior design context related to the feature area being discussed.\n24\t\n25\t**Step 3: Help refine the idea/feature**\n26\t\n27\tOnce you've become familiar with the project and code, you can start asking me questions, one at a time, to **help refine the idea**.\n28\t\n29\t**Detect active profiles before refining.** The design phase runs before any code exists, so file-based detection is impossible. Run the design interaction pattern from [shared-profile-detection.md §The `design` interaction pattern](shared-profile-detection.md) — it iterates all profiles with `## Design signals`, matches their declared tokens against the idea prose, and handles confirmation prompts. Never auto-activate a profile silently.\n30\t\n31\tFor each active profile, use the `Read` tool on `<plugin_root>/profiles/<name>/design/index.md` — where `<plugin_root>` is the absolute plugin-root path you already know from SKILL.md context. Skip silently if absent; not every profile populates a `design/` subdirectory. Load every file listed under **Always load**; a profile's `questions.md` (when present) seeds the refinement question pool. Integrate the profile's questions into the flow below — one question per message, as always.\n32\t\n33\tIdeally, the questions would be multiple choice, but open-ended questions are OK too.\n34\t\n35\tDon't forget: only one question per message!\n36\t\n37\t**Step 4: Describe the design**\n38\t\n39\tOnce you believe you understand what we're trying to achieve, stop and **describe the whole design** to me, **in sections of 200-300 words at a time**, **asking after each section whether it looks right so far**.\n40\t\n41\t**If the design recommends a specific library, SDK, framework, or API** — especially one not already in use in this project — apply the `dependency-handling` skill BEFORE committing to that recommendation. Verifying behavior against context7 at design time prevents proposing something that doesn't actually work the way you assumed.\n42\t\n43\t**Step 5: Document the design**\n44\t\n45\tDocument in .md files the entire design and write a comprehensive implementation plan.\n46\t\n47\tFeel free to break out the design/implementation documents into multi-part files, if necessary.\n48\t\n49\t**For each active profile** (from Step 3), re-consult `<plugin_root>/profiles/<name>/design/index.md` (using the same resolved plugin-root path you used in Step 3) and apply every always-load entry whose content shapes the final design document. Profile-contributed `sections.md` (when present) names required sections the design document must cover. Do not drop a required section silently; if a section genuinely does not apply, state so explicitly with a one-line justification.\n50\t\n51\tWhen creating documentation, follow this approach:\n52\t\n53\t- IF this is this a completely new feature - document it in in `/docs/wip/[feature-title]/{design,implementation}.md`.\n54\t- ELSE this an improvement or an addition to an existing feature:\n55\t  - If the feature is still WIP (documented under `/docs/wip`) - ask the user if you should update the existing design/implementation documents, or create new ones in a sub-directory of the existing feature.\n56\t  - Else the feature is completed (documented under root of `/docs`) - create new design/implementation documents in a sub-directory of the existing feature.\n57\t\n58\t**When documenting design and implementation plan**:\n59\t\n60\t- Assume the developer who is going to implement the feature is an experienced and highly-skilled %LANGUAGE% developer, but has zero context for our codebase, and knows almost nothing about our problem domain. Basically - a first-time contributor with a lot of programming experience in %LANGUAGE%.\n61\t- **Document everything the developer may need to know**: which files to touch for each task, code structure to be aware of, testing approaches, any potential docs they might need to check. Give them the whole plan as bite-sized tasks.\n62\t- **Make sure the plan is unambiguous, detailed and comprehensive** so the developer can adhere to DRY, YAGNI, TDD, atomic/self-contained commits principles when following this plan.\n63\t- **Pair each step with an explicit verification.** Every implementation step should name *how the developer will know it worked* — a specific test to run, a command whose output to check, or an observable behavior. Use the form `Step → verify: <check>`. Steps without a verification are a smell: either the step is too vague, or the work isn't really done when the step is.\n64\t\n65\tBut, of course, **DO NOT:**\n66\t\n67\t- **DO NOT add complete code examples**. The documentation should be a guideline that gives the developer all the information they may need when writing the actual code, not copy-paste code chunks.\n68\t- **DO NOT add commit message templates** to tasks, that the developer should use when committing the changes.\n69\t- **DO NOT add other small, generic details that do not bring value** and/or are not specifically relevant to this particular feature. For example, adding something like \"to run tests, execute: 'go test ./...'\" to a task does not bring value. Remember, the developer is experienced and skilled!\n70\t\n71\t**Capy index:** After documenting the design, index key architecture decisions and trade-offs as `kk:arch-decisions`. Only index non-obvious rationale — skip if the decisions are self-evident from the docs themselves.\n72\t\n73\t**Step 6: Create the task list**\n74\t\n75\tBased on the implementation plan documented in Step 5, create a `tasks.md` file in the same `/docs/wip/[feature-title]/` directory.\n76\t\n77\tFollow the structure and conventions in the [example task file](./example-tasks.md). Key points:\n78\t\n79\t- **Header metadata** links back to design/implementation docs and tracks overall feature status\n80\t- **One H2 per task** with status, dependencies, and a link to the relevant docs section\n81\t- **Checkbox subtasks** are concrete, actionable implementation steps — specific enough that a developer with no project context can follow them\n82\t- **Subtask descriptions** name the file/function/component being touched and what to do with it — not vague (\"implement auth\") but precise (\"create `internal/auth/token.go` with `GenerateToken` and `ValidateToken` functions\")\n83\t- **Dependencies** reference other tasks by number when ordering matters\n84\t- **Status values:** `pending`, `in-progress`, `done`, `blocked` (with reason)\n85\t- Tasks should map roughly 1:1 to atomic, self-contained commits\n86\t- **Always include a final verification task** that depends on all other tasks — it should invoke `test` to run the full test suite, `document` to update any relevant docs, `review-code` with project's language input to review the code, and `review-spec` to verify the implementation matches the design and implementation docs\n87\t"}]},"uuid":"391edf75-2c8a-4249-a8ab-0ef54fab789b","timestamp":"2026-04-23T18:21:53.450Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/skills/design/idea-process.md","content":"### Workflow\n\nCopy this checklist and check off items as you complete them:\n\n```\nTask Progress:\n- [ ] Step 1: Understand the current state of the project\n- [ ] Step 2: Check the documentation\n- [ ] Step 3: Help refine the idea/feature\n- [ ] Step 4: Describe the design\n- [ ] Step 5: Document the design\n- [ ] Step 6: Create the task list\n```\n\n**Step 1: Understand the current state of the project**\n\nTo properly refine the idea into a fully-formed design you need to **understand the existing code** in our working directory to know where we're starting off.\n\n**Step 2: Check the documentation**\n\nIn order to gain a better understanding of the project, **check the contributing guidelines and any relevant documentation**. For example, take a look at `CONTRIBUTING.md` and `docs` directory.\n\n**Capy search:** Before refining the idea, search `kk:arch-decisions` and `kk:project-conventions` for prior design context related to the feature area being discussed.\n\n**Step 3: Help refine the idea/feature**\n\nOnce you've become familiar with the project and code, you can start asking me questions, one at a time, to **help refine the idea**.\n\n**Detect active profiles before refining.** The design phase runs before any code exists, so file-based detection is impossible. Run the design interaction pattern from [shared-profile-detection.md §The `design` interaction pattern](shared-profile-detection.md) — it iterates all profiles with `## Design signals`, matches their declared tokens against the idea prose, and handles confirmation prompts. Never auto-activate a profile silently.\n\nFor each active profile, use the `Read` tool on `<plugin_root>/profiles/<name>/design/index.md` — where `<plugin_root>` is the absolute plugin-root path you already know from SKILL.md context. Skip silently if absent; not every profile populates a `design/` subdirectory. Load every file listed under **Always load**; a profile's `questions.md` (when present) seeds the refinement question pool. Integrate the profile's questions into the flow below — one question per message, as always.\n\nIdeally, the questions would be multiple choice, but open-ended questions are OK too.\n\nDon't forget: only one question per message!\n\n**Step 4: Describe the design**\n\nOnce you believe you understand what we're trying to achieve, stop and **describe the whole design** to me, **in sections of 200-300 words at a time**, **asking after each section whether it looks right so far**.\n\n**If the design recommends a specific library, SDK, framework, or API** — especially one not already in use in this project — apply the `dependency-handling` skill BEFORE committing to that recommendation. Verifying behavior against context7 at design time prevents proposing something that doesn't actually work the way you assumed.\n\n**Step 5: Document the design**\n\nDocument in .md files the entire design and write a comprehensive implementation plan.\n\nFeel free to break out the design/implementation documents into multi-part files, if necessary.\n\n**For each active profile** (from Step 3), re-consult `<plugin_root>/profiles/<name>/design/index.md` (using the same resolved plugin-root path you used in Step 3) and apply every always-load entry whose content shapes the final design document. Profile-contributed `sections.md` (when present) names required sections the design document must cover. Do not drop a required section silently; if a section genuinely does not apply, state so explicitly with a one-line justification.\n\nWhen creating documentation, follow this approach:\n\n- IF this is this a completely new feature - document it in in `/docs/wip/[feature-title]/{design,implementation}.md`.\n- ELSE this an improvement or an addition to an existing feature:\n  - If the feature is still WIP (documented under `/docs/wip`) - ask the user if you should update the existing design/implementation documents, or create new ones in a sub-directory of the existing feature.\n  - Else the feature is completed (documented under root of `/docs`) - create new design/implementation documents in a sub-directory of the existing feature.\n\n**When documenting design and implementation plan**:\n\n- Assume the developer who is going to implement the feature is an experienced and highly-skilled %LANGUAGE% developer, but has zero context for our codebase, and knows almost nothing about our problem domain. Basically - a first-time contributor with a lot of programming experience in %LANGUAGE%.\n- **Document everything the developer may need to know**: which files to touch for each task, code structure to be aware of, testing approaches, any potential docs they might need to check. Give them the whole plan as bite-sized tasks.\n- **Make sure the plan is unambiguous, detailed and comprehensive** so the developer can adhere to DRY, YAGNI, TDD, atomic/self-contained commits principles when following this plan.\n- **Pair each step with an explicit verification.** Every implementation step should name *how the developer will know it worked* — a specific test to run, a command whose output to check, or an observable behavior. Use the form `Step → verify: <check>`. Steps without a verification are a smell: either the step is too vague, or the work isn't really done when the step is.\n\nBut, of course, **DO NOT:**\n\n- **DO NOT add complete code examples**. The documentation should be a guideline that gives the developer all the information they may need when writing the actual code, not copy-paste code chunks.\n- **DO NOT add commit message templates** to tasks, that the developer should use when committing the changes.\n- **DO NOT add other small, generic details that do not bring value** and/or are not specifically relevant to this particular feature. For example, adding something like \"to run tests, execute: 'go test ./...'\" to a task does not bring value. Remember, the developer is experienced and skilled!\n\n**Capy index:** After documenting the design, index key architecture decisions and trade-offs as `kk:arch-decisions`. Only index non-obvious rationale — skip if the decisions are self-evident from the docs themselves.\n\n**Step 6: Create the task list**\n\nBased on the implementation plan documented in Step 5, create a `tasks.md` file in the same `/docs/wip/[feature-title]/` directory.\n\nFollow the structure and conventions in the [example task file](./example-tasks.md). Key points:\n\n- **Header metadata** links back to design/implementation docs and tracks overall feature status\n- **One H2 per task** with status, dependencies, and a link to the relevant docs section\n- **Checkbox subtasks** are concrete, actionable implementation steps — specific enough that a developer with no project context can follow them\n- **Subtask descriptions** name the file/function/component being touched and what to do with it — not vague (\"implement auth\") but precise (\"create `internal/auth/token.go` with `GenerateToken` and `ValidateToken` functions\")\n- **Dependencies** reference other tasks by number when ordering matters\n- **Status values:** `pending`, `in-progress`, `done`, `blocked` (with reason)\n- Tasks should map roughly 1:1 to atomic, self-contained commits\n- **Always include a final verification task** that depends on all other tasks — it should invoke `test` to run the full test suite, `document` to update any relevant docs, `review-code` with project's language input to review the code, and `review-spec` to verify the implementation matches the design and implementation docs\n","numLines":87,"startLine":1,"totalLines":87}},"sourceToolAssistantUUID":"e322c48a-aab8-428d-8b2c-f055e6bf472a","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"b602a914-8b3c-447d-8ff1-102a80b8c203","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Se34fKhvCcqofoiFsvY3z4","type":"tool_result","content":"1\t# Capy Knowledge Base Protocol\n2\t\n3\tIf `capy` MCP tools are not available in this session, skip all search and index steps below and proceed normally.\n4\t\n5\t## Source Label Taxonomy\n6\t\n7\tAll plugin-managed labels use the `kk:` namespace prefix.\n8\t\n9\t| Label                    | Contents                                                              |\n10\t| ------------------------ | --------------------------------------------------------------------- |\n11\t| `kk:arch-decisions`      | Architecture decisions, design rationale, trade-offs                  |\n12\t| `kk:review-findings`     | Code review patterns, recurring issues, anti-patterns                 |\n13\t| `kk:lang-idioms`         | Language best practices, idiomatic patterns from external sources     |\n14\t| `kk:project-conventions` | Discovered project patterns, naming conventions, structural decisions |\n15\t| `kk:test-patterns`       | Testing approaches, edge cases, test infrastructure decisions         |\n16\t| `kk:debug-context`       | Root causes, tricky bugs and their fixes, environment gotchas         |\n17\t\n18\t## Search Conventions\n19\t\n20\t- Use 2-4 specific terms per query — not vague keywords\n21\t- Always scope with `source` filter to relevant `kk:*` labels\n22\t- Use `source: \"kk:\"` only for broad cross-domain searches (e.g., CoVe verification)\n23\t- Default `limit: 3` per query unless more context is needed\n24\t- **Cold-start fallback:** If no results, proceed with standard guidelines — empty results are normal for new projects\n25\t\n26\t## Index Conventions\n27\t\n28\t- Only index non-obvious learnings not derivable from reading the code or git history\n29\t- Keep content concise — summarize the insight, don't dump raw output\n30\t- Always use a `kk:` prefixed label from the taxonomy above\n31\t- One concept per `capy_index` call — don't bundle unrelated learnings\n32\t- Skip indexing if the insight is already captured in design docs or CLAUDE.md\n33\t"}]},"uuid":"83ca6fb6-c9cf-44c1-bf5d-4dd2d2456444","timestamp":"2026-04-23T18:21:54.589Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/skills/design/shared-capy-knowledge-protocol.md","content":"# Capy Knowledge Base Protocol\n\nIf `capy` MCP tools are not available in this session, skip all search and index steps below and proceed normally.\n\n## Source Label Taxonomy\n\nAll plugin-managed labels use the `kk:` namespace prefix.\n\n| Label                    | Contents                                                              |\n| ------------------------ | --------------------------------------------------------------------- |\n| `kk:arch-decisions`      | Architecture decisions, design rationale, trade-offs                  |\n| `kk:review-findings`     | Code review patterns, recurring issues, anti-patterns                 |\n| `kk:lang-idioms`         | Language best practices, idiomatic patterns from external sources     |\n| `kk:project-conventions` | Discovered project patterns, naming conventions, structural decisions |\n| `kk:test-patterns`       | Testing approaches, edge cases, test infrastructure decisions         |\n| `kk:debug-context`       | Root causes, tricky bugs and their fixes, environment gotchas         |\n\n## Search Conventions\n\n- Use 2-4 specific terms per query — not vague keywords\n- Always scope with `source` filter to relevant `kk:*` labels\n- Use `source: \"kk:\"` only for broad cross-domain searches (e.g., CoVe verification)\n- Default `limit: 3` per query unless more context is needed\n- **Cold-start fallback:** If no results, proceed with standard guidelines — empty results are normal for new projects\n\n## Index Conventions\n\n- Only index non-obvious learnings not derivable from reading the code or git history\n- Keep content concise — summarize the insight, don't dump raw output\n- Always use a `kk:` prefixed label from the taxonomy above\n- One concept per `capy_index` call — don't bundle unrelated learnings\n- Skip indexing if the insight is already captured in design docs or CLAUDE.md\n","numLines":33,"startLine":1,"totalLines":33}},"sourceToolAssistantUUID":"b602a914-8b3c-447d-8ff1-102a80b8c203","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"dfe6ec4e-0a83-4cb1-84d0-8e907a3adb9c","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QbRH4EyxX2cECUD12iLCUv","type":"tool_result","content":"1\t## Profile detection procedure\n2\t\n3\tSingle source of truth for computing the set of profiles active in the current context.\n4\tConsumed by six skills: `review-code`, `review-spec`, `design`, `implement`, `test`, and `document`.\n5\t\n6\tEvery profile under `klaude-plugin/profiles/<name>/` declares its own trigger rule in `DETECTION.md` using the mandatory three-section schema (`## Path signals`, `## Filename signals`, `## Content signals`).\n7\tThe shared procedure below applies the same algorithm against every profile's declared values.\n8\t\n9\t### Inputs per consuming skill\n10\t\n11\tNot every consumer has a diff available. Use the input listed for your skill:\n12\t\n13\t- **`review-code`** — git diff (staged, or an explicit commit range). Scope is\n14\t  the set of files the diff touches.\n15\t- **`review-spec`** — git diff when invoked standalone; the feature directory's\n16\t  full file list when invoked by `implement` (spec review runs over the whole\n17\t  feature, not just the current task's diff).\n18\t- **`test`** — git diff mid-feature, OR the feature directory's file list\n19\t  post-implementation.\n20\t- **`implement`** — the current sub-task's target file list, augmented by the\n21\t  diff accumulated so far in the feature.\n22\t- **`design`** — **no file list available** (implementation does not yet exist).\n23\t  Detection uses a user-declared or keyword-inferred signal instead; see\n24\t  [The `design` interaction pattern](#the-design-interaction-pattern) below.\n25\t- **`document`** — feature directory's current file list; diff optional.\n26\t\n27\t### The `design` interaction pattern\n28\t\n29\tThe design phase runs before any code exists, so file-based detection is impossible. Detection uses idea-prose keyword matching against tokens declared in each profile's `DETECTION.md`.\n30\t\n31\t**Algorithm:**\n32\t\n33\t1. **Collect tokens.** Iterate §Known profiles. For each `<name>`, `Read` `<plugin_root>/profiles/<name>/DETECTION.md`. If the file has no `## Design signals` section, skip — that profile does not participate in design-phase detection. Otherwise, parse `display_name` and `tokens` from the section.\n34\t2. **Build union.** Collect all declared tokens into a single set, each tagged by its source profile name and `display_name`.\n35\t3. **Match.** Check the idea prose against the union. Matching is case-insensitive, whole-word (so `pod` in \"podcast\" does not fire).\n36\t4. **Confirm.** On match, surface a confirmation prompt per matched profile:\n37\t   *\"This appears to be a {display_name} feature. Activate the {profile_name} profile?\"* — let the user confirm yes/no. When multiple profiles match, confirm each independently.\n38\t5. **Fallback.** If no token matches but the idea is **ambiguous** — names infrastructure, deployment, runtime, or platform concerns without naming a specific technology (e.g., _\"add a caching layer for the service\"_, _\"build a CI pipeline\"_, _\"deploy to production\"_); or includes overloaded tokens that collide across domains — build the fallback prompt dynamically from all profiles that declare `## Design signals`:\n39\t   *\"Does this feature involve {display_name_1, display_name_2, ...}? If yes, which?\"*\n40\t\n41\tConfirmation is required — the design skill never auto-activates a profile silently. The narrow per-profile token sets avoid noisy false positives from tokens that overload across domains.\n42\t\n43\tOnce activated, subsequent design-phase steps treat the profile as active in the same record shape produced by file-based detection (see §Output shape).\n44\t\n45\t### Known profiles\n46\t\n47\tThis is the authoritative enumeration of profile `<name>`s — do NOT try discover profiles via any other means.\n48\tAn explicit list is boring, deterministic, and unambiguous; runtime filesystem enumeration against the plugin tree has proven unreliable.\n49\t\n50\t- `go`\n51\t- `python`\n52\t- `java`\n53\t- `js_ts`\n54\t- `kotlin`\n55\t- `k8s`\n56\t- `k8s-operator`\n57\t\n58\t### Algorithm\n59\t\n60\tThroughout this procedure, `<plugin_root>` denotes the absolute plugin-root path the agent already knows from the SKILL.md that invoked the procedure. Use that resolved absolute path wherever `<plugin_root>` appears.\n61\t\n62\t1. **Iterate profiles.** For each §Known profiles `<name>`:\n63\t   1. Use the `Read` tool on `<plugin_root>/profiles/<name>/DETECTION.md`.\n64\t   2. If `Read` fails with ENOENT (profile name in list but directory missing — a stale list entry), skip silently and move on.\n65\t   3. If `Read` succeeds, parse the declared `## Path signals`, `## Filename signals`, and `## Content signals` sections.\n66\t\n67\t2. **Evaluate in cost order.** For each input file, check signals in this order: path → filename → content. Cheapest first.\n68\t3. **Apply the authority rule.** A file activates the profile only if a **filename signal** OR **content signal** matches.\n69\t   A path-only match does NOT activate. Paths are a pre-filter that promotes files to \"candidates\"; authoritative activation requires filename or content confirmation.\n70\t   A file that matches NO path signal is still evaluated against filename and content signals — path pre-filtering is a cost hint, not a gate.\n71\t   (Otherwise a `Chart.yaml` at a non-standard path would be missed.)\n72\t4. **Bound content inspection.** Read at most ~16 KB per file when evaluating content signals.\n73\t   Multi-document YAML is inspected per `---`-separated block — a file may have five blocks, and only the third need match for the file to activate the profile.\n74\t5. **Collect records.** Accumulate one record per matched profile with the triggering files and the signal descriptions that fired.\n75\t\n76\t### Tool choice\n77\t\n78\t- Single file at `<plugin_root>/…` → `Read`. This is what the algorithm uses.\n79\t- Enumeration across profiles → iterate the §Known profiles list, `Read` each. Never `Glob` (cwd-scoped, misses outside-cwd paths).\n80\t\n81\t### Two dimensions: cost vs authority\n82\t\n83\tSignals live on two axes that point in different directions. Keep them separate in your mental model:\n84\t\n85\t- **Evaluation cost** (cheapest first): path < filename < content.\n86\t  Path globs touch only the path string;\n87\t  filename matches are exact string compares;\n88\t  content inspection opens the file.\n89\t- **Authority** (most authoritative first): filename ≈ content > path.\n90\t  A filename or content match activates the profile; a path-only match does not.\n91\t  Filename and content are equally authoritative, but filename resolves first at runtime — a filename match short-circuits content inspection for that file.\n92\t\n93\tEvaluating cheapest-first optimizes work. Applying authority correctly prevents false positives from incidental path matches — a stray `manifests/` directory in a Go project does not make the project Kubernetes.\n94\t\n95\t### Plugin-root resolution failure\n96\t\n97\tIf every `Read` attempt in Algorithm step 1 fails — i.e., `<plugin_root>` could not be resolved from SKILL.md context, or the paths do not exist — the procedure cannot continue.\n98\t\n99\tOn that failure:\n100\t\n101\t1. Emit an actionable error pointing to `CLAUDE.md` §Profile Conventions.\n102\t2. Return an empty result set so the calling skill falls back to generic guidance rather than panicking.\n103\t3. Do not retry; do not silently guess a path.\n104\t\n105\tConsumers inherit this check by invoking the shared procedure — no skill re-implements it.\n106\t\n107\t### Output shape\n108\t\n109\tA list of records, one per matched profile:\n110\t\n111\t```\n112\t[\n113\t  {\n114\t    profile: \"<name>\",                     // directory name under profiles/\n115\t    triggered_by: [\n116\t      \"filename: Chart.yaml\",              // signal type + matched value\n117\t      \"content: apiVersion+kind in block 2\"\n118\t    ],\n119\t    files: [\n120\t      \"path/to/file1.yaml\",\n121\t      \"path/to/file2.yaml\"\n122\t    ]\n123\t  },\n124\t  ...\n125\t]\n126\t```\n127\t\n128\tField semantics:\n129\t\n130\t- `profile` — the directory name under `profiles/` (e.g., `go`, `python`, `k8s`).\n131\t  Used downstream to resolve `profiles/<profile>/<phase>/index.md`,\n132\t  where `<phase>` is the profile phase subdirectory named identically to the calling skill:\n133\t  `review-code/`, `review-spec/`, `design/`, `implement/`, `test/`, or `document/`.\n134\t- `triggered_by` — which signal type fired and the specific value that matched.\n135\t  For debugging and for explaining detection to the user; never used as the key for profile lookup.\n136\t- `files` — the subset of input files that activated this profile.\n137\t  Skills use this to scope behavior (e.g., `helm lint` runs only on files triggered under Helm filename signals, not on every YAML in the diff).\n138\t\n139\tWhen no profile matches, return the empty list `[]`. The caller falls back to generic guidance, identical to today's \"no language detected\" path.\n140\t"}]},"uuid":"958512c0-927d-4616-a3c5-0c68b78ceaf1","timestamp":"2026-04-23T18:21:56.080Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/skills/design/shared-profile-detection.md","content":"## Profile detection procedure\n\nSingle source of truth for computing the set of profiles active in the current context.\nConsumed by six skills: `review-code`, `review-spec`, `design`, `implement`, `test`, and `document`.\n\nEvery profile under `klaude-plugin/profiles/<name>/` declares its own trigger rule in `DETECTION.md` using the mandatory three-section schema (`## Path signals`, `## Filename signals`, `## Content signals`).\nThe shared procedure below applies the same algorithm against every profile's declared values.\n\n### Inputs per consuming skill\n\nNot every consumer has a diff available. Use the input listed for your skill:\n\n- **`review-code`** — git diff (staged, or an explicit commit range). Scope is\n  the set of files the diff touches.\n- **`review-spec`** — git diff when invoked standalone; the feature directory's\n  full file list when invoked by `implement` (spec review runs over the whole\n  feature, not just the current task's diff).\n- **`test`** — git diff mid-feature, OR the feature directory's file list\n  post-implementation.\n- **`implement`** — the current sub-task's target file list, augmented by the\n  diff accumulated so far in the feature.\n- **`design`** — **no file list available** (implementation does not yet exist).\n  Detection uses a user-declared or keyword-inferred signal instead; see\n  [The `design` interaction pattern](#the-design-interaction-pattern) below.\n- **`document`** — feature directory's current file list; diff optional.\n\n### The `design` interaction pattern\n\nThe design phase runs before any code exists, so file-based detection is impossible. Detection uses idea-prose keyword matching against tokens declared in each profile's `DETECTION.md`.\n\n**Algorithm:**\n\n1. **Collect tokens.** Iterate §Known profiles. For each `<name>`, `Read` `<plugin_root>/profiles/<name>/DETECTION.md`. If the file has no `## Design signals` section, skip — that profile does not participate in design-phase detection. Otherwise, parse `display_name` and `tokens` from the section.\n2. **Build union.** Collect all declared tokens into a single set, each tagged by its source profile name and `display_name`.\n3. **Match.** Check the idea prose against the union. Matching is case-insensitive, whole-word (so `pod` in \"podcast\" does not fire).\n4. **Confirm.** On match, surface a confirmation prompt per matched profile:\n   *\"This appears to be a {display_name} feature. Activate the {profile_name} profile?\"* — let the user confirm yes/no. When multiple profiles match, confirm each independently.\n5. **Fallback.** If no token matches but the idea is **ambiguous** — names infrastructure, deployment, runtime, or platform concerns without naming a specific technology (e.g., _\"add a caching layer for the service\"_, _\"build a CI pipeline\"_, _\"deploy to production\"_); or includes overloaded tokens that collide across domains — build the fallback prompt dynamically from all profiles that declare `## Design signals`:\n   *\"Does this feature involve {display_name_1, display_name_2, ...}? If yes, which?\"*\n\nConfirmation is required — the design skill never auto-activates a profile silently. The narrow per-profile token sets avoid noisy false positives from tokens that overload across domains.\n\nOnce activated, subsequent design-phase steps treat the profile as active in the same record shape produced by file-based detection (see §Output shape).\n\n### Known profiles\n\nThis is the authoritative enumeration of profile `<name>`s — do NOT try discover profiles via any other means.\nAn explicit list is boring, deterministic, and unambiguous; runtime filesystem enumeration against the plugin tree has proven unreliable.\n\n- `go`\n- `python`\n- `java`\n- `js_ts`\n- `kotlin`\n- `k8s`\n- `k8s-operator`\n\n### Algorithm\n\nThroughout this procedure, `<plugin_root>` denotes the absolute plugin-root path the agent already knows from the SKILL.md that invoked the procedure. Use that resolved absolute path wherever `<plugin_root>` appears.\n\n1. **Iterate profiles.** For each §Known profiles `<name>`:\n   1. Use the `Read` tool on `<plugin_root>/profiles/<name>/DETECTION.md`.\n   2. If `Read` fails with ENOENT (profile name in list but directory missing — a stale list entry), skip silently and move on.\n   3. If `Read` succeeds, parse the declared `## Path signals`, `## Filename signals`, and `## Content signals` sections.\n\n2. **Evaluate in cost order.** For each input file, check signals in this order: path → filename → content. Cheapest first.\n3. **Apply the authority rule.** A file activates the profile only if a **filename signal** OR **content signal** matches.\n   A path-only match does NOT activate. Paths are a pre-filter that promotes files to \"candidates\"; authoritative activation requires filename or content confirmation.\n   A file that matches NO path signal is still evaluated against filename and content signals — path pre-filtering is a cost hint, not a gate.\n   (Otherwise a `Chart.yaml` at a non-standard path would be missed.)\n4. **Bound content inspection.** Read at most ~16 KB per file when evaluating content signals.\n   Multi-document YAML is inspected per `---`-separated block — a file may have five blocks, and only the third need match for the file to activate the profile.\n5. **Collect records.** Accumulate one record per matched profile with the triggering files and the signal descriptions that fired.\n\n### Tool choice\n\n- Single file at `<plugin_root>/…` → `Read`. This is what the algorithm uses.\n- Enumeration across profiles → iterate the §Known profiles list, `Read` each. Never `Glob` (cwd-scoped, misses outside-cwd paths).\n\n### Two dimensions: cost vs authority\n\nSignals live on two axes that point in different directions. Keep them separate in your mental model:\n\n- **Evaluation cost** (cheapest first): path < filename < content.\n  Path globs touch only the path string;\n  filename matches are exact string compares;\n  content inspection opens the file.\n- **Authority** (most authoritative first): filename ≈ content > path.\n  A filename or content match activates the profile; a path-only match does not.\n  Filename and content are equally authoritative, but filename resolves first at runtime — a filename match short-circuits content inspection for that file.\n\nEvaluating cheapest-first optimizes work. Applying authority correctly prevents false positives from incidental path matches — a stray `manifests/` directory in a Go project does not make the project Kubernetes.\n\n### Plugin-root resolution failure\n\nIf every `Read` attempt in Algorithm step 1 fails — i.e., `<plugin_root>` could not be resolved from SKILL.md context, or the paths do not exist — the procedure cannot continue.\n\nOn that failure:\n\n1. Emit an actionable error pointing to `CLAUDE.md` §Profile Conventions.\n2. Return an empty result set so the calling skill falls back to generic guidance rather than panicking.\n3. Do not retry; do not silently guess a path.\n\nConsumers inherit this check by invoking the shared procedure — no skill re-implements it.\n\n### Output shape\n\nA list of records, one per matched profile:\n\n```\n[\n  {\n    profile: \"<name>\",                     // directory name under profiles/\n    triggered_by: [\n      \"filename: Chart.yaml\",              // signal type + matched value\n      \"content: apiVersion+kind in block 2\"\n    ],\n    files: [\n      \"path/to/file1.yaml\",\n      \"path/to/file2.yaml\"\n    ]\n  },\n  ...\n]\n```\n\nField semantics:\n\n- `profile` — the directory name under `profiles/` (e.g., `go`, `python`, `k8s`).\n  Used downstream to resolve `profiles/<profile>/<phase>/index.md`,\n  where `<phase>` is the profile phase subdirectory named identically to the calling skill:\n  `review-code/`, `review-spec/`, `design/`, `implement/`, `test/`, or `document/`.\n- `triggered_by` — which signal type fired and the specific value that matched.\n  For debugging and for explaining detection to the user; never used as the key for profile lookup.\n- `files` — the subset of input files that activated this profile.\n  Skills use this to scope behavior (e.g., `helm lint` runs only on files triggered under Helm filename signals, not on every YAML in the diff).\n\nWhen no profile matches, return the empty list `[]`. 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 {"parentUuid":"46cf8320-8ca0-4b83-b4cd-a406517c9e97","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WvCauBFqYbgJMsnYXgFAg9","type":"tool_result","content":"1\t# Tasks: JWT Authentication System\n2\t\n3\t> Design: [./design.md](./design.md)\n4\t> Implementation: [./implementation.md](./implementation.md)\n5\t> Status: in-progress\n6\t> Created: 2026-03-11\n7\t\n8\t## Task 1: Token generation and validation library\n9\t- **Status:** done\n10\t- **Depends on:** —\n11\t- **Docs:** [implementation.md#token-library](./implementation.md#token-library)\n12\t\n13\t### Subtasks\n14\t- [x] 1.1 Create `internal/auth/token.go` with `GenerateToken(userID, role)` and `ValidateToken(tokenString)` functions\n15\t- [x] 1.2 Add token expiry configuration via `internal/config/auth.go` — read from env vars with sensible defaults\n16\t- [x] 1.3 Write table-driven tests covering: valid token, expired token, malformed token, wrong signing key\n17\t\n18\t## Task 2: Auth middleware\n19\t- **Status:** in-progress\n20\t- **Depends on:** Task 1\n21\t- **Docs:** [implementation.md#middleware](./implementation.md#middleware)\n22\t\n23\t### Subtasks\n24\t- [x] 2.1 Create `internal/middleware/auth.go` — extract token from `Authorization: Bearer <token>` header, validate via token library, inject user claims into request context\n25\t- [ ] 2.2 Add middleware to router in `cmd/server/routes.go` for all `/api/v1/*` routes except `/api/v1/auth/login`\n26\t- [ ] 2.3 Integration tests: request without token → 401, expired token → 401, valid token → passes through with claims in context\n27\t\n28\t## Task 3: Login and refresh endpoints\n29\t- **Status:** pending\n30\t- **Depends on:** Task 1, Task 2\n31\t- **Docs:** [implementation.md#endpoints](./implementation.md#endpoints)\n32\t\n33\t### Subtasks\n34\t- [ ] 3.1 `POST /api/v1/auth/login` — accept email/password, verify against user store, return access + refresh tokens\n35\t- [ ] 3.2 `POST /api/v1/auth/refresh` — accept refresh token, validate, return new access token\n36\t- [ ] 3.3 Tests: valid credentials → tokens returned, invalid credentials → 401, expired refresh token → 401\n37\t\n38\t## Task 4: Password hashing migration\n39\t- **Status:** blocked\n40\t- **Depends on:** —\n41\t- **Docs:** [design.md#password-storage](./design.md#password-storage)\n42\t- **Blocked:** Waiting on DB migration tooling decision (see design.md#open-questions)\n43\t\n44\t### Subtasks\n45\t- [ ] 4.1 Add bcrypt hashing to `internal/auth/password.go` with cost factor from config\n46\t- [ ] 4.2 Create migration to add `password_hash` column to users table\n47\t- [ ] 4.3 Update user registration flow to hash passwords on create\n48\t\n49\t## Task 5: Final verification\n50\t- **Status:** pending\n51\t- **Depends on:** Task 1, Task 2, Task 3, Task 4\n52\t\n53\t### Subtasks\n54\t- [ ] 5.1 Run `test` skill to verify all tasks — full test suite, integration tests, edge cases\n55\t- [ ] 5.2 Run `document` skill to update any relevant docs\n56\t- [ ] 5.3 Run `review-code` skill with the project language input to review the implementation\n57\t- [ ] 5.4 Run `review-spec` skill to verify implementation matches design and implementation docs\n58\t"}]},"uuid":"56a12174-25a7-49d1-8786-0d16a0f76b7c","timestamp":"2026-04-23T18:22:09.133Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/skills/design/example-tasks.md","content":"# Tasks: JWT Authentication System\n\n> Design: [./design.md](./design.md)\n> Implementation: [./implementation.md](./implementation.md)\n> Status: in-progress\n> Created: 2026-03-11\n\n## Task 1: Token generation and validation library\n- **Status:** done\n- **Depends on:** —\n- **Docs:** [implementation.md#token-library](./implementation.md#token-library)\n\n### Subtasks\n- [x] 1.1 Create `internal/auth/token.go` with `GenerateToken(userID, role)` and `ValidateToken(tokenString)` functions\n- [x] 1.2 Add token expiry configuration via `internal/config/auth.go` — read from env vars with sensible defaults\n- [x] 1.3 Write table-driven tests covering: valid token, expired token, malformed token, wrong signing key\n\n## Task 2: Auth middleware\n- **Status:** in-progress\n- **Depends on:** Task 1\n- **Docs:** [implementation.md#middleware](./implementation.md#middleware)\n\n### Subtasks\n- [x] 2.1 Create `internal/middleware/auth.go` — extract token from `Authorization: Bearer <token>` header, validate via token library, inject user claims into request context\n- [ ] 2.2 Add middleware to router in `cmd/server/routes.go` for all `/api/v1/*` routes except `/api/v1/auth/login`\n- [ ] 2.3 Integration tests: request without token → 401, expired token → 401, valid token → passes through with claims in context\n\n## Task 3: Login and refresh endpoints\n- **Status:** pending\n- **Depends on:** Task 1, Task 2\n- **Docs:** [implementation.md#endpoints](./implementation.md#endpoints)\n\n### Subtasks\n- [ ] 3.1 `POST /api/v1/auth/login` — accept email/password, verify against user store, return access + refresh tokens\n- [ ] 3.2 `POST /api/v1/auth/refresh` — accept refresh token, validate, return new access token\n- [ ] 3.3 Tests: valid credentials → tokens returned, invalid credentials → 401, expired refresh token → 401\n\n## Task 4: Password hashing migration\n- **Status:** blocked\n- **Depends on:** —\n- **Docs:** [design.md#password-storage](./design.md#password-storage)\n- **Blocked:** Waiting on DB migration tooling decision (see design.md#open-questions)\n\n### Subtasks\n- [ ] 4.1 Add bcrypt hashing to `internal/auth/password.go` with cost factor from config\n- [ ] 4.2 Create migration to add `password_hash` column to users table\n- [ ] 4.3 Update user registration flow to hash passwords on create\n\n## Task 5: Final verification\n- **Status:** pending\n- **Depends on:** Task 1, Task 2, Task 3, Task 4\n\n### Subtasks\n- [ ] 5.1 Run `test` skill to verify all tasks — full test suite, integration tests, edge cases\n- [ ] 5.2 Run `document` skill to update any relevant docs\n- [ ] 5.3 Run `review-code` skill with the project language input to review the implementation\n- [ ] 5.4 Run `review-spec` skill to verify implementation matches design and implementation docs\n","numLines":58,"startLine":1,"totalLines":58}},"sourceToolAssistantUUID":"46cf8320-8ca0-4b83-b4cd-a406517c9e97","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"a9804d8a-4f3e-436f-b4b5-7b94aea05035","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_018JYhmpHLrJCJFSAKBHjnVx","type":"tool_result","content":"1\t# Go — detection\n2\t\n3\tDeclares when the `go` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n4\t\n5\t## Path signals\n6\t\n7\t_None._ Go detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n8\t\n9\t## Filename signals\n10\t\n11\t_None._ Go detection is extension-based, not filename-based.\n12\t\n13\t## Content signals\n14\t\n15\tA file activates the Go profile if its extension is `.go`. The extension match is authoritative; no byte-level content inspection is required.\n16\t"}]},"uuid":"feafc703-2384-4e3e-9965-c252065472ec","timestamp":"2026-04-23T18:43:45.046Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/go/DETECTION.md","content":"# Go — detection\n\nDeclares when the `go` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n\n## Path signals\n\n_None._ Go detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n\n## Filename signals\n\n_None._ Go detection is extension-based, not filename-based.\n\n## Content signals\n\nA file activates the Go profile if its extension is `.go`. The extension match is authoritative; no byte-level content inspection is required.\n","numLines":16,"startLine":1,"totalLines":16}},"sourceToolAssistantUUID":"a9804d8a-4f3e-436f-b4b5-7b94aea05035","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"010cf2ad-ca14-4907-be58-c308f2aab02f","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WCx9pPJbmJDas2jUg88d3N","type":"tool_result","content":"1\t# Python — detection\n2\t\n3\tDeclares when the `python` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n4\t\n5\t## Path signals\n6\t\n7\t_None._ Python detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n8\t\n9\t## Filename signals\n10\t\n11\t_None._ Python detection is extension-based, not filename-based.\n12\t\n13\t## Content signals\n14\t\n15\tA file activates the Python profile if its extension is one of: `.py`, `.pyi`. The extension match is authoritative; no byte-level content inspection is required.\n16\t"}]},"uuid":"8d576ddc-44d1-4de6-a992-801748ce2916","timestamp":"2026-04-23T18:43:49.734Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/python/DETECTION.md","content":"# Python — detection\n\nDeclares when the `python` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n\n## Path signals\n\n_None._ Python detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n\n## Filename signals\n\n_None._ Python detection is extension-based, not filename-based.\n\n## Content signals\n\nA file activates the Python profile if its extension is one of: `.py`, `.pyi`. The extension match is authoritative; no byte-level content inspection is required.\n","numLines":16,"startLine":1,"totalLines":16}},"sourceToolAssistantUUID":"010cf2ad-ca14-4907-be58-c308f2aab02f","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"157cfe8c-3bf0-4f32-ba28-d3ee2c0877a5","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013ocrPUgoEZyj9QZd8XhfE7","type":"tool_result","content":"1\t# Kubernetes — detection\n2\t\n3\tDeclares when the `k8s` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Detection is additive: multiple profiles may activate on the same diff (e.g., `go` + `k8s`).\n4\t\n5\tEvaluation follows the shared cost-ordered procedure (path → filename → content). Authority runs filename ≈ content > path: filename or content signals activate the profile; path alone never does, it only promotes a file to a candidate.\n6\t\n7\t## Path signals\n8\t\n9\tCase-insensitive substring match anywhere in the file's path. Pre-filter only — a path hit alone does NOT activate the profile.\n10\t\n11\t- `k8s/`\n12\t- `manifests/`\n13\t- `charts/`\n14\t- `kustomize/`\n15\t- `deploy/`\n16\t- `templates/`\n17\t\n18\t## Filename signals\n19\t\n20\tAuthoritative: any match activates the profile. Filename matches short-circuit content inspection for the matched file.\n21\t\n22\t- `Chart.yaml` (exact) → Helm chart root.\n23\t- Any filename starting with `values` (e.g., `values.yaml`, `values.yml`, `values-prod.yaml`, `values-prod-v2-final.yaml`) when the containing directory also contains `Chart.yaml` → Helm values by adjacency. The `values*` glob has no upper bound on the wildcard; the adjacency rule (sibling `Chart.yaml` in the same directory) is the binding constraint. The match is filename-plus-adjacency only — file content is not inspected, so a file named `values-backup.yaml` next to a `Chart.yaml` activates regardless of what it actually contains.\n24\t- Any file with extension `.yaml`, `.yml`, or `.tpl` inside `<dir>/templates/` where `<dir>` itself contains a `Chart.yaml` as a direct child → Helm template. The binding constraint is that the `templates/` directory must sit *directly* next to a `Chart.yaml` — i.e., at a chart root or a subchart root under `<parent>/charts/<subchart>/`. A `templates/` nested elsewhere in the tree (e.g., `docs/templates/`, `ci/templates/`) does NOT activate this rule even when a `Chart.yaml` sits at the repository root, because `docs/` and `ci/` do not themselves contain a `Chart.yaml`. This avoids the monorepo false-positive where a repo-root umbrella `Chart.yaml` would otherwise claim every `templates/` directory in the tree. It still avoids the trap where a standalone edit to `<chart-root>/templates/deployment.yaml` contains `{{ if ... }}` directives before any `apiVersion:` and would otherwise fail the content signal.\n25\t- Exact filenames `kustomization.yaml`, `kustomization.yml`, or `Kustomization` → Kustomize.\n26\t\n27\t## Content signals\n28\t\n29\tAuthoritative for generic YAML files (`.yaml` or `.yml`) not already caught by a filename signal. Inspection is bounded to the first ~16 KB per file; large generated manifests beyond that bound are not inspected.\n30\t\n31\t- Split the file on `---` document separators. For each `---`-separated document block, check for a top-level `apiVersion:` AND a top-level `kind:` — parsed as YAML mapping keys at zero indent, not as substrings inside block scalars (`|`, `>`) or comments. A block satisfying both is a Kubernetes manifest document.\n32\t- One matching document activates the profile for that file. The first document need not match — a file whose second or later document is the only K8s document still activates.\n33\t- A `.yaml` / `.yml` file with no matching document in any block → not Kubernetes. (It may still match another profile; generic YAML belongs to no profile by default.)\n34\t\n35\t---\n36\t\n37\t## Multi-profile behavior\n38\t\n39\tThe Kubernetes profile is **additive**. It coexists with programming-language profiles or any other IaC profile on the same diff. When Go source files sit alongside Kubernetes manifests, both `go` and `k8s` activate; downstream skills consult both profiles' content and emit findings grouped by `(profile, checklist)`.\n40\t\n41\t## Design signals\n42\t\n43\tdisplay_name: Kubernetes\n44\ttokens:\n45\t  - Kubernetes\n46\t  - K8s\n47\t  - Helm chart\n48\t  - kubectl\n49\t  - kustomize\n50\t  - manifest.yaml\n51\t  - Deployment resource\n52\t  - StatefulSet\n53\t  - DaemonSet\n54\t  - CronJob\n55\t\n56\t## Dockerfile non-trigger\n57\t\n58\tA Dockerfile on its own — even under a `deploy/` or `k8s/` directory — does NOT activate the `k8s` profile. Dockerfiles match no filename signal here (they are not `Chart.yaml` / `values*.yaml` / `kustomization.yaml`) and no content signal (they do not contain `apiVersion:` + `kind:`). When a Dockerfile appears in the same diff as Kubernetes manifests, `k8s` activates on the manifests' signals; the Dockerfile itself is not reviewed by this profile. A future container profile may own Dockerfiles independently.\n59\t"}]},"uuid":"8c5153a6-b89b-41ee-bf24-8a41d71973f5","timestamp":"2026-04-23T18:43:50.685Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/k8s/DETECTION.md","content":"# Kubernetes — detection\n\nDeclares when the `k8s` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Detection is additive: multiple profiles may activate on the same diff (e.g., `go` + `k8s`).\n\nEvaluation follows the shared cost-ordered procedure (path → filename → content). Authority runs filename ≈ content > path: filename or content signals activate the profile; path alone never does, it only promotes a file to a candidate.\n\n## Path signals\n\nCase-insensitive substring match anywhere in the file's path. Pre-filter only — a path hit alone does NOT activate the profile.\n\n- `k8s/`\n- `manifests/`\n- `charts/`\n- `kustomize/`\n- `deploy/`\n- `templates/`\n\n## Filename signals\n\nAuthoritative: any match activates the profile. Filename matches short-circuit content inspection for the matched file.\n\n- `Chart.yaml` (exact) → Helm chart root.\n- Any filename starting with `values` (e.g., `values.yaml`, `values.yml`, `values-prod.yaml`, `values-prod-v2-final.yaml`) when the containing directory also contains `Chart.yaml` → Helm values by adjacency. The `values*` glob has no upper bound on the wildcard; the adjacency rule (sibling `Chart.yaml` in the same directory) is the binding constraint. The match is filename-plus-adjacency only — file content is not inspected, so a file named `values-backup.yaml` next to a `Chart.yaml` activates regardless of what it actually contains.\n- Any file with extension `.yaml`, `.yml`, or `.tpl` inside `<dir>/templates/` where `<dir>` itself contains a `Chart.yaml` as a direct child → Helm template. The binding constraint is that the `templates/` directory must sit *directly* next to a `Chart.yaml` — i.e., at a chart root or a subchart root under `<parent>/charts/<subchart>/`. A `templates/` nested elsewhere in the tree (e.g., `docs/templates/`, `ci/templates/`) does NOT activate this rule even when a `Chart.yaml` sits at the repository root, because `docs/` and `ci/` do not themselves contain a `Chart.yaml`. This avoids the monorepo false-positive where a repo-root umbrella `Chart.yaml` would otherwise claim every `templates/` directory in the tree. It still avoids the trap where a standalone edit to `<chart-root>/templates/deployment.yaml` contains `{{ if ... }}` directives before any `apiVersion:` and would otherwise fail the content signal.\n- Exact filenames `kustomization.yaml`, `kustomization.yml`, or `Kustomization` → Kustomize.\n\n## Content signals\n\nAuthoritative for generic YAML files (`.yaml` or `.yml`) not already caught by a filename signal. Inspection is bounded to the first ~16 KB per file; large generated manifests beyond that bound are not inspected.\n\n- Split the file on `---` document separators. For each `---`-separated document block, check for a top-level `apiVersion:` AND a top-level `kind:` — parsed as YAML mapping keys at zero indent, not as substrings inside block scalars (`|`, `>`) or comments. A block satisfying both is a Kubernetes manifest document.\n- One matching document activates the profile for that file. The first document need not match — a file whose second or later document is the only K8s document still activates.\n- A `.yaml` / `.yml` file with no matching document in any block → not Kubernetes. (It may still match another profile; generic YAML belongs to no profile by default.)\n\n---\n\n## Multi-profile behavior\n\nThe Kubernetes profile is **additive**. It coexists with programming-language profiles or any other IaC profile on the same diff. When Go source files sit alongside Kubernetes manifests, both `go` and `k8s` activate; downstream skills consult both profiles' content and emit findings grouped by `(profile, checklist)`.\n\n## Design signals\n\ndisplay_name: Kubernetes\ntokens:\n  - Kubernetes\n  - K8s\n  - Helm chart\n  - kubectl\n  - kustomize\n  - manifest.yaml\n  - Deployment resource\n  - StatefulSet\n  - DaemonSet\n  - CronJob\n\n## Dockerfile non-trigger\n\nA Dockerfile on its own — even under a `deploy/` or `k8s/` directory — does NOT activate the `k8s` profile. Dockerfiles match no filename signal here (they are not `Chart.yaml` / `values*.yaml` / `kustomization.yaml`) and no content signal (they do not contain `apiVersion:` + `kind:`). When a Dockerfile appears in the same diff as Kubernetes manifests, `k8s` activates on the manifests' signals; the Dockerfile itself is not reviewed by this profile. A future container profile may own Dockerfiles independently.\n","numLines":59,"startLine":1,"totalLines":59}},"sourceToolAssistantUUID":"157cfe8c-3bf0-4f32-ba28-d3ee2c0877a5","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"d43f3d89-b24e-4ffb-81ff-d25bf3ada32b","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0169iEygyfa8r5U15suxsGBG","type":"tool_result","content":"1\t# JS/TS — detection\n2\t\n3\tDeclares when the `js_ts` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n4\t\n5\tThe profile covers JavaScript and TypeScript jointly: review concerns (typing, async, modules, React patterns) overlap substantially, and the ecosystem tools (npm, bundlers, Node/browser runtimes) are shared.\n6\t\n7\t## Path signals\n8\t\n9\t_None._ JS/TS detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n10\t\n11\t## Filename signals\n12\t\n13\t_None._ JS/TS detection is extension-based, not filename-based.\n14\t\n15\t## Content signals\n16\t\n17\tA file activates the JS/TS profile if its extension is one of: `.js`, `.jsx`, `.mjs`, `.cjs`, `.ts`, `.tsx`, `.mts`, `.cts`. The extension match is authoritative; no byte-level content inspection is required.\n18\t"}]},"uuid":"70a761bb-c12c-4f8a-92b6-c138f8d80b07","timestamp":"2026-04-23T18:43:51.569Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/js_ts/DETECTION.md","content":"# JS/TS — detection\n\nDeclares when the `js_ts` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n\nThe profile covers JavaScript and TypeScript jointly: review concerns (typing, async, modules, React patterns) overlap substantially, and the ecosystem tools (npm, bundlers, Node/browser runtimes) are shared.\n\n## Path signals\n\n_None._ JS/TS detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n\n## Filename signals\n\n_None._ JS/TS detection is extension-based, not filename-based.\n\n## Content signals\n\nA file activates the JS/TS profile if its extension is one of: `.js`, `.jsx`, `.mjs`, `.cjs`, `.ts`, `.tsx`, `.mts`, `.cts`. The extension match is authoritative; no byte-level content inspection is required.\n","numLines":18,"startLine":1,"totalLines":18}},"sourceToolAssistantUUID":"d43f3d89-b24e-4ffb-81ff-d25bf3ada32b","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"b707f869-b682-40d2-b3cd-4502709a9252","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01L8aYfGqoz4jrWDAaD9GyJg","type":"tool_result","content":"1\t# Java — detection\n2\t\n3\tDeclares when the `java` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n4\t\n5\t## Path signals\n6\t\n7\t_None._ Java detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n8\t\n9\t## Filename signals\n10\t\n11\t_None._ Java detection is extension-based, not filename-based.\n12\t\n13\t## Content signals\n14\t\n15\tA file activates the Java profile if its extension is `.java`. The extension match is authoritative; no byte-level content inspection is required.\n16\t"}]},"uuid":"2c7ad8e6-e23b-4d09-a4f6-a3a3b880c116","timestamp":"2026-04-23T18:43:52.219Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/java/DETECTION.md","content":"# Java — detection\n\nDeclares when the `java` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n\n## Path signals\n\n_None._ Java detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n\n## Filename signals\n\n_None._ Java detection is extension-based, not filename-based.\n\n## Content signals\n\nA file activates the Java profile if its extension is `.java`. The extension match is authoritative; no byte-level content inspection is required.\n","numLines":16,"startLine":1,"totalLines":16}},"sourceToolAssistantUUID":"b707f869-b682-40d2-b3cd-4502709a9252","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"796b53cb-4c1d-4511-bcaf-dd005838bd2c","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WWyZf6ybkqNox854MW6rjX","type":"tool_result","content":"1\t# Kotlin — detection\n2\t\n3\tDeclares when the `kotlin` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n4\t\n5\t## Path signals\n6\t\n7\t_None._ Kotlin detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n8\t\n9\t## Filename signals\n10\t\n11\t_None._ Kotlin detection is extension-based, not filename-based.\n12\t\n13\t## Content signals\n14\t\n15\tA file activates the Kotlin profile if its extension is one of: `.kt`, `.kts`. The extension match is authoritative; no byte-level content inspection is required.\n16\t"}]},"uuid":"782c6ca8-282f-49e8-b2fe-98c2a8840f9f","timestamp":"2026-04-23T18:43:53.399Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/kotlin/DETECTION.md","content":"# Kotlin — detection\n\nDeclares when the `kotlin` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Multiple profiles may activate additively on the same diff.\n\n## Path signals\n\n_None._ Kotlin detection does not use path heuristics; file extension alone is authoritative (see Content signals).\n\n## Filename signals\n\n_None._ Kotlin detection is extension-based, not filename-based.\n\n## Content signals\n\nA file activates the Kotlin profile if its extension is one of: `.kt`, `.kts`. The extension match is authoritative; no byte-level content inspection is required.\n","numLines":16,"startLine":1,"totalLines":16}},"sourceToolAssistantUUID":"796b53cb-4c1d-4511-bcaf-dd005838bd2c","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"43067949-97bb-409c-8578-5e031fe1cd6b","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_019mSKFi2cAUXuWMGUDAWJJf","type":"tool_result","content":"1\t# Kubernetes Operator — detection\n2\t\n3\tDeclares when the `k8s-operator` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Detection is additive: an operator project typically activates both `k8s-operator` (for controller code) and `k8s` (for the manifests it generates/deploys).\n4\t\n5\tEvaluation follows the shared cost-ordered procedure (path → filename → content). Authority runs filename ≈ content > path: filename or content signals activate the profile; path alone never does, it only promotes a file to a candidate.\n6\t\n7\t## Path signals\n8\t\n9\tCase-insensitive substring match anywhere in the file's path. Pre-filter only — a path hit alone does NOT activate the profile.\n10\t\n11\t- `internal/controller/`\n12\t- `api/`\n13\t- `controllers/`\n14\t\n15\t## Filename signals\n16\t\n17\tAuthoritative: any match activates the profile. Filename matches short-circuit content inspection for the matched file.\n18\t\n19\t- `PROJECT` (exact) → kubebuilder project marker. This file is generated by `kubebuilder init` and contains the project's domain, layout, and plugin metadata. Its mere presence signals an operator project.\n20\t- Any file under `config/crd/` → CRD kustomize bases generated by `controller-gen`.\n21\t- Any file under `config/webhook/` → admission/conversion webhook kustomize configuration.\n22\t\n23\t## Content signals\n24\t\n25\tAuthoritative for files not already caught by a filename signal. Inspection is bounded to the first ~16 KB per file.\n26\t\n27\t- A `Makefile` containing the literal string `controller-gen` OR a target named `manifests` (line starting with `manifests:`) → kubebuilder/operator-sdk generated Makefile with CRD/RBAC generation targets.\n28\t- A Go source file (`.go` extension) containing an import of `sigs.k8s.io/controller-runtime` → controller-runtime dependency, the standard library for writing Kubernetes controllers.\n29\t\n30\t## Design signals\n31\t\n32\tdisplay_name: Kubernetes Operator\n33\ttokens:\n34\t  - operator\n35\t  - controller\n36\t  - kubebuilder\n37\t  - controller-runtime\n38\t  - CRD authoring\n39\t  - custom resource definition authoring\n40\t  - reconciliation loop\n41\t"}]},"uuid":"62b1e1ac-e6af-45f3-bb0a-092763fc6742","timestamp":"2026-04-23T18:43:54.446Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/.claude/plugins/cache/claude-toolbox/kk/0.10.0-rc.6/profiles/k8s-operator/DETECTION.md","content":"# Kubernetes Operator — detection\n\nDeclares when the `k8s-operator` profile activates on a given set of files. Consumed by `klaude-plugin/skills/_shared/profile-detection.md`. Detection is additive: an operator project typically activates both `k8s-operator` (for controller code) and `k8s` (for the manifests it generates/deploys).\n\nEvaluation follows the shared cost-ordered procedure (path → filename → content). Authority runs filename ≈ content > path: filename or content signals activate the profile; path alone never does, it only promotes a file to a candidate.\n\n## Path signals\n\nCase-insensitive substring match anywhere in the file's path. Pre-filter only — a path hit alone does NOT activate the profile.\n\n- `internal/controller/`\n- `api/`\n- `controllers/`\n\n## Filename signals\n\nAuthoritative: any match activates the profile. Filename matches short-circuit content inspection for the matched file.\n\n- `PROJECT` (exact) → kubebuilder project marker. This file is generated by `kubebuilder init` and contains the project's domain, layout, and plugin metadata. Its mere presence signals an operator project.\n- Any file under `config/crd/` → CRD kustomize bases generated by `controller-gen`.\n- Any file under `config/webhook/` → admission/conversion webhook kustomize configuration.\n\n## Content signals\n\nAuthoritative for files not already caught by a filename signal. Inspection is bounded to the first ~16 KB per file.\n\n- A `Makefile` containing the literal string `controller-gen` OR a target named `manifests` (line starting with `manifests:`) → kubebuilder/operator-sdk generated Makefile with CRD/RBAC generation targets.\n- A Go source file (`.go` extension) containing an import of `sigs.k8s.io/controller-runtime` → controller-runtime dependency, the standard library for writing Kubernetes controllers.\n\n## Design signals\n\ndisplay_name: Kubernetes Operator\ntokens:\n  - operator\n  - controller\n  - kubebuilder\n  - controller-runtime\n  - CRD authoring\n  - custom resource definition authoring\n  - reconciliation loop\n","numLines":41,"startLine":1,"totalLines":41}},"sourceToolAssistantUUID":"43067949-97bb-409c-8578-5e031fe1cd6b","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"32fc8f19-12a7-47db-8191-6e7b03d5068d","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FePrRPWk1Kjp1Tkk3NavGD","type":"tool_result","content":"1\tpackage store\n2\t\n3\timport (\n4\t\t\"encoding/json\"\n5\t\t\"fmt\"\n6\t\t\"maps\"\n7\t\t\"regexp\"\n8\t\t\"slices\"\n9\t\t\"strings\"\n10\t)\n11\t\n12\tconst maxChunkBytes = 4096\n13\t\n14\tvar (\n15\t\theadingRe    = regexp.MustCompile(`^(#{1,4})\\s+(.+)$`)\n16\t\thorizRuleRe  = regexp.MustCompile(`^[-_*]{3,}\\s*$`)\n17\t\tcodeFenceRe  = regexp.MustCompile(\"^`{3,}\")\n18\t\tblankLineRe  = regexp.MustCompile(`\\n\\s*\\n`)\n19\t\tcodeBlockRe  = regexp.MustCompile(\"(?s)```\\\\w*\\n[\\\\s\\\\S]*?```\")\n20\t)\n21\t\n22\t// chunkMarkdown splits markdown content by headings with code-block awareness.\n23\tfunc chunkMarkdown(content string, maxBytes int) []Chunk {\n24\t\tif maxBytes <= 0 {\n25\t\t\tmaxBytes = maxChunkBytes\n26\t\t}\n27\t\n28\t\tlines := strings.Split(content, \"\\n\")\n29\t\tvar chunks []Chunk\n30\t\tvar currentLines []string\n31\t\tvar headingStack [4]string // H1-H4\n32\t\tinFence := false\n33\t\n34\t\tflush := func() {\n35\t\t\tif len(currentLines) == 0 {\n36\t\t\t\treturn\n37\t\t\t}\n38\t\t\ttext := strings.Join(currentLines, \"\\n\")\n39\t\t\ttext = strings.TrimSpace(text)\n40\t\t\tif text == \"\" {\n41\t\t\t\tcurrentLines = nil\n42\t\t\t\treturn\n43\t\t\t}\n44\t\t\ttitle := buildHeadingTitle(headingStack)\n45\t\t\thasCode := chunkHasCode(text)\n46\t\t\tif len(text) <= maxBytes {\n47\t\t\t\tchunks = append(chunks, Chunk{Title: title, Content: text, HasCode: hasCode})\n48\t\t\t} else {\n49\t\t\t\tchunks = append(chunks, splitOversized(text, title, maxBytes)...)\n50\t\t\t}\n51\t\t\tcurrentLines = nil\n52\t\t}\n53\t\n54\t\tfor _, line := range lines {\n55\t\t\ttrimmed := strings.TrimSpace(line)\n56\t\n57\t\t\t// Track code fence state.\n58\t\t\tif codeFenceRe.MatchString(trimmed) {\n59\t\t\t\tinFence = !inFence\n60\t\t\t\tcurrentLines = append(currentLines, line)\n61\t\t\t\tcontinue\n62\t\t\t}\n63\t\n64\t\t\tif inFence {\n65\t\t\t\tcurrentLines = append(currentLines, line)\n66\t\t\t\tcontinue\n67\t\t\t}\n68\t\n69\t\t\t// Horizontal rule — flush.\n70\t\t\tif horizRuleRe.MatchString(trimmed) {\n71\t\t\t\tflush()\n72\t\t\t\tcontinue\n73\t\t\t}\n74\t\n75\t\t\t// Heading — flush and update stack.\n76\t\t\tif m := headingRe.FindStringSubmatch(trimmed); m != nil {\n77\t\t\t\tflush()\n78\t\t\t\tlevel := len(m[1]) // 1-4\n79\t\t\t\theadingStack[level-1] = m[2]\n80\t\t\t\t// Clear deeper levels.\n81\t\t\t\tfor i := level; i < 4; i++ {\n82\t\t\t\t\theadingStack[i] = \"\"\n83\t\t\t\t}\n84\t\t\t\tcontinue\n85\t\t\t}\n86\t\n87\t\t\tcurrentLines = append(currentLines, line)\n88\t\t}\n89\t\tflush()\n90\t\n91\t\tif len(chunks) == 0 && strings.TrimSpace(content) != \"\" {\n92\t\t\tchunks = append(chunks, Chunk{\n93\t\t\t\tTitle:   \"Content\",\n94\t\t\t\tContent: strings.TrimSpace(content),\n95\t\t\t\tHasCode: chunkHasCode(content),\n96\t\t\t})\n97\t\t}\n98\t\n99\t\treturn chunks\n100\t}\n101\t\n102\tfunc buildHeadingTitle(stack [4]string) string {\n103\t\tvar parts []string\n104\t\tfor _, h := range stack {\n105\t\t\tif h != \"\" {\n106\t\t\t\tparts = append(parts, h)\n107\t\t\t}\n108\t\t}\n109\t\tif len(parts) == 0 {\n110\t\t\treturn \"Content\"\n111\t\t}\n112\t\treturn strings.Join(parts, \" > \")\n113\t}\n114\t\n115\t// splitOversized splits a chunk that exceeds maxBytes at paragraph boundaries.\n116\tfunc splitOversized(text, title string, maxBytes int) []Chunk {\n117\t\tparagraphs := blankLineRe.Split(text, -1)\n118\t\tvar chunks []Chunk\n119\t\tvar buf strings.Builder\n120\t\toverlap := \"\"\n121\t\n122\t\tfor _, para := range paragraphs {\n123\t\t\tpara = strings.TrimSpace(para)\n124\t\t\tif para == \"\" {\n125\t\t\t\tcontinue\n126\t\t\t}\n127\t\t\tif buf.Len() > 0 && buf.Len()+len(para)+2 > maxBytes {\n128\t\t\t\tcontent := buf.String()\n129\t\t\t\tchunks = append(chunks, Chunk{\n130\t\t\t\t\tTitle:   title,\n131\t\t\t\t\tContent: content,\n132\t\t\t\t\tHasCode: chunkHasCode(content),\n133\t\t\t\t})\n134\t\t\t\t// Keep last 2 lines as overlap.\n135\t\t\t\tlines := strings.Split(content, \"\\n\")\n136\t\t\t\tif len(lines) > 2 {\n137\t\t\t\t\toverlap = strings.Join(lines[len(lines)-2:], \"\\n\")\n138\t\t\t\t} else {\n139\t\t\t\t\toverlap = content\n140\t\t\t\t}\n141\t\t\t\tbuf.Reset()\n142\t\t\t\tif overlap != \"\" {\n143\t\t\t\t\tbuf.WriteString(overlap)\n144\t\t\t\t\tbuf.WriteString(\"\\n\\n\")\n145\t\t\t\t}\n146\t\t\t}\n147\t\t\tif buf.Len() > 0 {\n148\t\t\t\tbuf.WriteString(\"\\n\\n\")\n149\t\t\t}\n150\t\t\tbuf.WriteString(para)\n151\t\t}\n152\t\n153\t\tif buf.Len() > 0 {\n154\t\t\tcontent := buf.String()\n155\t\t\tchunks = append(chunks, Chunk{\n156\t\t\t\tTitle:   title,\n157\t\t\t\tContent: content,\n158\t\t\t\tHasCode: chunkHasCode(content),\n159\t\t\t})\n160\t\t}\n161\t\treturn chunks\n162\t}\n163\t\n164\tfunc chunkHasCode(content string) bool {\n165\t\treturn codeBlockRe.MatchString(content)\n166\t}\n167\t\n168\t// chunkPlainText splits plain text using blank-line or fixed-line strategies.\n169\tfunc chunkPlainText(content string, linesPerChunk int) []Chunk {\n170\t\tif linesPerChunk <= 0 {\n171\t\t\tlinesPerChunk = 20\n172\t\t}\n173\t\n174\t\tlines := strings.Split(content, \"\\n\")\n175\t\n176\t\t// Single chunk if small enough.\n177\t\tif len(lines) <= linesPerChunk {\n178\t\t\treturn []Chunk{{Title: \"Output\", Content: strings.TrimSpace(content)}}\n179\t\t}\n180\t\n181\t\t// Phase 1: try blank-line splitting.\n182\t\tsections := blankLineRe.Split(content, -1)\n183\t\tif len(sections) >= 3 && len(sections) <= 200 && allUnder(sections, 5000) {\n184\t\t\tvar chunks []Chunk\n185\t\t\tfor i, sec := range sections {\n186\t\t\t\tsec = strings.TrimSpace(sec)\n187\t\t\t\tif sec == \"\" {\n188\t\t\t\t\tcontinue\n189\t\t\t\t}\n190\t\t\t\ttitle := firstLine(sec, 80)\n191\t\t\t\tif title == \"\" {\n192\t\t\t\t\ttitle = fmt.Sprintf(\"Section %d\", i+1)\n193\t\t\t\t}\n194\t\t\t\tchunks = append(chunks, Chunk{Title: title, Content: sec})\n195\t\t\t}\n196\t\t\treturn chunks\n197\t\t}\n198\t\n199\t\t// Phase 2: fixed-line groups with overlap.\n200\t\tconst overlap = 2\n201\t\tstep := max(linesPerChunk-overlap, 1)\n202\t\tvar chunks []Chunk\n203\t\tfor i := 0; i < len(lines); i += step {\n204\t\t\tend := min(i+linesPerChunk, len(lines))\n205\t\t\tslice := lines[i:end]\n206\t\t\ttext := strings.Join(slice, \"\\n\")\n207\t\t\ttext = strings.TrimSpace(text)\n208\t\t\tif text == \"\" {\n209\t\t\t\tcontinue\n210\t\t\t}\n211\t\t\ttitle := firstLine(text, 80)\n212\t\t\tif title == \"\" {\n213\t\t\t\ttitle = fmt.Sprintf(\"Lines %d-%d\", i+1, end)\n214\t\t\t}\n215\t\t\tchunks = append(chunks, Chunk{Title: title, Content: text})\n216\t\t\tif end == len(lines) {\n217\t\t\t\tbreak\n218\t\t\t}\n219\t\t}\n220\t\treturn chunks\n221\t}\n222\t\n223\tfunc allUnder(sections []string, maxBytes int) bool {\n224\t\tfor _, s := range sections {\n225\t\t\tif len(s) > maxBytes {\n226\t\t\t\treturn false\n227\t\t\t}\n228\t\t}\n229\t\treturn true\n230\t}\n231\t\n232\tfunc firstLine(text string, maxLen int) string {\n233\t\tline, _, _ := strings.Cut(text, \"\\n\")\n234\t\tline = strings.TrimSpace(line)\n235\t\tif len(line) > maxLen {\n236\t\t\tline = line[:maxLen]\n237\t\t}\n238\t\treturn line\n239\t}\n240\t\n241\t// walkJSON recursively chunks a parsed JSON value.\n242\tfunc walkJSON(v any, path []string, maxBytes int) []Chunk {\n243\t\tif maxBytes <= 0 {\n244\t\t\tmaxBytes = maxChunkBytes\n245\t\t}\n246\t\n247\t\tswitch val := v.(type) {\n248\t\tcase map[string]any:\n249\t\t\treturn chunkJSONObject(val, path, maxBytes)\n250\t\tcase []any:\n251\t\t\tprefix := \"(root)\"\n252\t\t\tif len(path) > 0 {\n253\t\t\t\tprefix = strings.Join(path, \" > \")\n254\t\t\t}\n255\t\t\treturn chunkJSONArray(val, prefix, maxBytes)\n256\t\tdefault:\n257\t\t\t// Primitive.\n258\t\t\tserialized, _ := json.Marshal(val)\n259\t\t\tif len(serialized) > maxBytes {\n260\t\t\t\ttitle := \"(root)\"\n261\t\t\t\tif len(path) > 0 {\n262\t\t\t\t\ttitle = strings.Join(path, \" > \")\n263\t\t\t\t}\n264\t\t\t\treturn []Chunk{{Title: title, Content: string(serialized)}}\n265\t\t\t}\n266\t\t\treturn nil\n267\t\t}\n268\t}\n269\t\n270\tfunc chunkJSONObject(obj map[string]any, path []string, maxBytes int) []Chunk {\n271\t\t// Check if flat (no nested objects/arrays).\n272\t\tflat := true\n273\t\tfor _, v := range obj {\n274\t\t\tswitch v.(type) {\n275\t\t\tcase map[string]any, []any:\n276\t\t\t\tflat = false\n277\t\t\t}\n278\t\t\tif !flat {\n279\t\t\t\tbreak\n280\t\t\t}\n281\t\t}\n282\t\n283\t\tserialized, _ := json.MarshalIndent(obj, \"\", \"  \")\n284\t\n285\t\tif flat && len(serialized) < maxBytes {\n286\t\t\ttitle := \"(root)\"\n287\t\t\tif len(path) > 0 {\n288\t\t\t\ttitle = strings.Join(path, \" > \")\n289\t\t\t}\n290\t\t\treturn []Chunk{{Title: title, Content: string(serialized), HasCode: true}}\n291\t\t}\n292\t\n293\t\t// Recurse into each key in sorted order for deterministic output.\n294\t\tvar chunks []Chunk\n295\t\tfor _, key := range slices.Sorted(maps.Keys(obj)) {\n296\t\t\tval := obj[key]\n297\t\t\tchildPath := append(append([]string{}, path...), key)\n298\t\t\tsub := walkJSON(val, childPath, maxBytes)\n299\t\t\tif len(sub) == 0 {\n300\t\t\t\t// Small primitive — emit inline.\n301\t\t\t\ts, _ := json.Marshal(val)\n302\t\t\t\ttitle := strings.Join(childPath, \" > \")\n303\t\t\t\tchunks = append(chunks, Chunk{Title: title, Content: string(s), HasCode: true})\n304\t\t\t} else {\n305\t\t\t\tchunks = append(chunks, sub...)\n306\t\t\t}\n307\t\t}\n308\t\treturn chunks\n309\t}\n310\t\n311\tfunc chunkJSONArray(arr []any, prefix string, maxBytes int) []Chunk {\n312\t\tif len(arr) == 0 {\n313\t\t\treturn nil\n314\t\t}\n315\t\n316\t\tidField := findIdentityField(arr)\n317\t\tvar chunks []Chunk\n318\t\tvar batch []any\n319\t\tbatchSize := 0\n320\t\tstartIdx := 0\n321\t\n322\t\tflushBatch := func(endIdx int) {\n323\t\t\tif len(batch) == 0 {\n324\t\t\t\treturn\n325\t\t\t}\n326\t\t\tserialized, _ := json.MarshalIndent(batch, \"\", \"  \")\n327\t\t\ttitle := jsonBatchTitle(prefix, batch, idField, startIdx, endIdx)\n328\t\t\tchunks = append(chunks, Chunk{Title: title, Content: string(serialized), HasCode: true})\n329\t\t}\n330\t\n331\t\tfor i, item := range arr {\n332\t\t\ts, _ := json.Marshal(item)\n333\t\t\titemSize := len(s)\n334\t\n335\t\t\tif batchSize > 0 && batchSize+itemSize > maxBytes && len(batch) > 0 {\n336\t\t\t\tflushBatch(startIdx + len(batch) - 1)\n337\t\t\t\tbatch = nil\n338\t\t\t\tbatchSize = 0\n339\t\t\t\tstartIdx = i\n340\t\t\t}\n341\t\n342\t\t\tbatch = append(batch, item)\n343\t\t\tbatchSize += itemSize\n344\t\t}\n345\t\tflushBatch(startIdx + len(batch) - 1)\n346\t\n347\t\treturn chunks\n348\t}\n349\t\n350\tfunc findIdentityField(arr []any) string {\n351\t\tif len(arr) == 0 {\n352\t\t\treturn \"\"\n353\t\t}\n354\t\tobj, ok := arr[0].(map[string]any)\n355\t\tif !ok {\n356\t\t\treturn \"\"\n357\t\t}\n358\t\tcandidates := []string{\"id\", \"name\", \"title\", \"path\", \"slug\", \"key\", \"label\"}\n359\t\tfor _, field := range candidates {\n360\t\t\tif v, exists := obj[field]; exists {\n361\t\t\t\tswitch v.(type) {\n362\t\t\t\tcase string, float64, int:\n363\t\t\t\t\treturn field\n364\t\t\t\t}\n365\t\t\t}\n366\t\t}\n367\t\treturn \"\"\n368\t}\n369\t\n370\tfunc jsonBatchTitle(prefix string, batch []any, idField string, startIdx, endIdx int) string {\n371\t\tif idField != \"\" {\n372\t\t\tids := extractIDs(batch, idField)\n373\t\t\tswitch len(ids) {\n374\t\t\tcase 1:\n375\t\t\t\treturn fmt.Sprintf(\"%s > %s\", prefix, ids[0])\n376\t\t\tcase 2, 3:\n377\t\t\t\treturn fmt.Sprintf(\"%s > %s\", prefix, strings.Join(ids, \", \"))\n378\t\t\tdefault:\n379\t\t\t\tif len(ids) > 0 {\n380\t\t\t\t\treturn fmt.Sprintf(\"%s > %s…%s\", prefix, ids[0], ids[len(ids)-1])\n381\t\t\t\t}\n382\t\t\t}\n383\t\t}\n384\t\tif startIdx == endIdx {\n385\t\t\treturn fmt.Sprintf(\"%s > [%d]\", prefix, startIdx)\n386\t\t}\n387\t\treturn fmt.Sprintf(\"%s > [%d-%d]\", prefix, startIdx, endIdx)\n388\t}\n389\t\n390\tfunc extractIDs(batch []any, field string) []string {\n391\t\tvar ids []string\n392\t\tfor _, item := range batch {\n393\t\t\tif obj, ok := item.(map[string]any); ok {\n394\t\t\t\tif v, exists := obj[field]; exists {\n395\t\t\t\t\tids = append(ids, fmt.Sprintf(\"%v\", v))\n396\t\t\t\t}\n397\t\t\t}\n398\t\t}\n399\t\treturn ids\n400\t}\n401\t"}]},"uuid":"9213ae55-47fc-419d-b438-8f452cb71054","timestamp":"2026-04-23T18:44:11.293Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/chunk.go","content":"package store\n\nimport (\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"maps\"\n\t\"regexp\"\n\t\"slices\"\n\t\"strings\"\n)\n\nconst maxChunkBytes = 4096\n\nvar (\n\theadingRe    = regexp.MustCompile(`^(#{1,4})\\s+(.+)$`)\n\thorizRuleRe  = regexp.MustCompile(`^[-_*]{3,}\\s*$`)\n\tcodeFenceRe  = regexp.MustCompile(\"^`{3,}\")\n\tblankLineRe  = regexp.MustCompile(`\\n\\s*\\n`)\n\tcodeBlockRe  = regexp.MustCompile(\"(?s)```\\\\w*\\n[\\\\s\\\\S]*?```\")\n)\n\n// chunkMarkdown splits markdown content by headings with code-block awareness.\nfunc chunkMarkdown(content string, maxBytes int) []Chunk {\n\tif maxBytes <= 0 {\n\t\tmaxBytes = maxChunkBytes\n\t}\n\n\tlines := strings.Split(content, \"\\n\")\n\tvar chunks []Chunk\n\tvar currentLines []string\n\tvar headingStack [4]string // H1-H4\n\tinFence := false\n\n\tflush := func() {\n\t\tif len(currentLines) == 0 {\n\t\t\treturn\n\t\t}\n\t\ttext := strings.Join(currentLines, \"\\n\")\n\t\ttext = strings.TrimSpace(text)\n\t\tif text == \"\" {\n\t\t\tcurrentLines = nil\n\t\t\treturn\n\t\t}\n\t\ttitle := buildHeadingTitle(headingStack)\n\t\thasCode := chunkHasCode(text)\n\t\tif len(text) <= maxBytes {\n\t\t\tchunks = append(chunks, Chunk{Title: title, Content: text, HasCode: hasCode})\n\t\t} else {\n\t\t\tchunks = append(chunks, splitOversized(text, title, maxBytes)...)\n\t\t}\n\t\tcurrentLines = nil\n\t}\n\n\tfor _, line := range lines {\n\t\ttrimmed := strings.TrimSpace(line)\n\n\t\t// Track code fence state.\n\t\tif codeFenceRe.MatchString(trimmed) {\n\t\t\tinFence = !inFence\n\t\t\tcurrentLines = append(currentLines, line)\n\t\t\tcontinue\n\t\t}\n\n\t\tif inFence {\n\t\t\tcurrentLines = append(currentLines, line)\n\t\t\tcontinue\n\t\t}\n\n\t\t// Horizontal rule — flush.\n\t\tif horizRuleRe.MatchString(trimmed) {\n\t\t\tflush()\n\t\t\tcontinue\n\t\t}\n\n\t\t// Heading — flush and update stack.\n\t\tif m := headingRe.FindStringSubmatch(trimmed); m != nil {\n\t\t\tflush()\n\t\t\tlevel := len(m[1]) // 1-4\n\t\t\theadingStack[level-1] = m[2]\n\t\t\t// Clear deeper levels.\n\t\t\tfor i := level; i < 4; i++ {\n\t\t\t\theadingStack[i] = \"\"\n\t\t\t}\n\t\t\tcontinue\n\t\t}\n\n\t\tcurrentLines = append(currentLines, line)\n\t}\n\tflush()\n\n\tif len(chunks) == 0 && strings.TrimSpace(content) != \"\" {\n\t\tchunks = append(chunks, Chunk{\n\t\t\tTitle:   \"Content\",\n\t\t\tContent: strings.TrimSpace(content),\n\t\t\tHasCode: chunkHasCode(content),\n\t\t})\n\t}\n\n\treturn chunks\n}\n\nfunc buildHeadingTitle(stack [4]string) string {\n\tvar parts []string\n\tfor _, h := range stack {\n\t\tif h != \"\" {\n\t\t\tparts = append(parts, h)\n\t\t}\n\t}\n\tif len(parts) == 0 {\n\t\treturn \"Content\"\n\t}\n\treturn strings.Join(parts, \" > \")\n}\n\n// splitOversized splits a chunk that exceeds maxBytes at paragraph boundaries.\nfunc splitOversized(text, title string, maxBytes int) []Chunk {\n\tparagraphs := blankLineRe.Split(text, -1)\n\tvar chunks []Chunk\n\tvar buf strings.Builder\n\toverlap := \"\"\n\n\tfor _, para := range paragraphs {\n\t\tpara = strings.TrimSpace(para)\n\t\tif para == \"\" {\n\t\t\tcontinue\n\t\t}\n\t\tif buf.Len() > 0 && buf.Len()+len(para)+2 > maxBytes {\n\t\t\tcontent := buf.String()\n\t\t\tchunks = append(chunks, Chunk{\n\t\t\t\tTitle:   title,\n\t\t\t\tContent: content,\n\t\t\t\tHasCode: chunkHasCode(content),\n\t\t\t})\n\t\t\t// Keep last 2 lines as overlap.\n\t\t\tlines := strings.Split(content, \"\\n\")\n\t\t\tif len(lines) > 2 {\n\t\t\t\toverlap = strings.Join(lines[len(lines)-2:], \"\\n\")\n\t\t\t} else {\n\t\t\t\toverlap = content\n\t\t\t}\n\t\t\tbuf.Reset()\n\t\t\tif overlap != \"\" {\n\t\t\t\tbuf.WriteString(overlap)\n\t\t\t\tbuf.WriteString(\"\\n\\n\")\n\t\t\t}\n\t\t}\n\t\tif buf.Len() > 0 {\n\t\t\tbuf.WriteString(\"\\n\\n\")\n\t\t}\n\t\tbuf.WriteString(para)\n\t}\n\n\tif buf.Len() > 0 {\n\t\tcontent := buf.String()\n\t\tchunks = append(chunks, Chunk{\n\t\t\tTitle:   title,\n\t\t\tContent: content,\n\t\t\tHasCode: chunkHasCode(content),\n\t\t})\n\t}\n\treturn chunks\n}\n\nfunc chunkHasCode(content string) bool {\n\treturn codeBlockRe.MatchString(content)\n}\n\n// chunkPlainText splits plain text using blank-line or fixed-line strategies.\nfunc chunkPlainText(content string, linesPerChunk int) []Chunk {\n\tif linesPerChunk <= 0 {\n\t\tlinesPerChunk = 20\n\t}\n\n\tlines := strings.Split(content, \"\\n\")\n\n\t// Single chunk if small enough.\n\tif len(lines) <= linesPerChunk {\n\t\treturn []Chunk{{Title: \"Output\", Content: strings.TrimSpace(content)}}\n\t}\n\n\t// Phase 1: try blank-line splitting.\n\tsections := blankLineRe.Split(content, -1)\n\tif len(sections) >= 3 && len(sections) <= 200 && allUnder(sections, 5000) {\n\t\tvar chunks []Chunk\n\t\tfor i, sec := range sections {\n\t\t\tsec = strings.TrimSpace(sec)\n\t\t\tif sec == \"\" {\n\t\t\t\tcontinue\n\t\t\t}\n\t\t\ttitle := firstLine(sec, 80)\n\t\t\tif title == \"\" {\n\t\t\t\ttitle = fmt.Sprintf(\"Section %d\", i+1)\n\t\t\t}\n\t\t\tchunks = append(chunks, Chunk{Title: title, Content: sec})\n\t\t}\n\t\treturn chunks\n\t}\n\n\t// Phase 2: fixed-line groups with overlap.\n\tconst overlap = 2\n\tstep := max(linesPerChunk-overlap, 1)\n\tvar chunks []Chunk\n\tfor i := 0; i < len(lines); i += step {\n\t\tend := min(i+linesPerChunk, len(lines))\n\t\tslice := lines[i:end]\n\t\ttext := strings.Join(slice, \"\\n\")\n\t\ttext = strings.TrimSpace(text)\n\t\tif text == \"\" {\n\t\t\tcontinue\n\t\t}\n\t\ttitle := firstLine(text, 80)\n\t\tif title == \"\" {\n\t\t\ttitle = fmt.Sprintf(\"Lines %d-%d\", i+1, end)\n\t\t}\n\t\tchunks = append(chunks, Chunk{Title: title, Content: text})\n\t\tif end == len(lines) {\n\t\t\tbreak\n\t\t}\n\t}\n\treturn chunks\n}\n\nfunc allUnder(sections []string, maxBytes int) bool {\n\tfor _, s := range sections {\n\t\tif len(s) > maxBytes {\n\t\t\treturn false\n\t\t}\n\t}\n\treturn true\n}\n\nfunc firstLine(text string, maxLen int) string {\n\tline, _, _ := strings.Cut(text, \"\\n\")\n\tline = strings.TrimSpace(line)\n\tif len(line) > maxLen {\n\t\tline = line[:maxLen]\n\t}\n\treturn line\n}\n\n// walkJSON recursively chunks a parsed JSON value.\nfunc walkJSON(v any, path []string, maxBytes int) []Chunk {\n\tif maxBytes <= 0 {\n\t\tmaxBytes = maxChunkBytes\n\t}\n\n\tswitch val := v.(type) {\n\tcase map[string]any:\n\t\treturn chunkJSONObject(val, path, maxBytes)\n\tcase []any:\n\t\tprefix := \"(root)\"\n\t\tif len(path) > 0 {\n\t\t\tprefix = strings.Join(path, \" > \")\n\t\t}\n\t\treturn chunkJSONArray(val, prefix, maxBytes)\n\tdefault:\n\t\t// Primitive.\n\t\tserialized, _ := json.Marshal(val)\n\t\tif len(serialized) > maxBytes {\n\t\t\ttitle := \"(root)\"\n\t\t\tif len(path) > 0 {\n\t\t\t\ttitle = strings.Join(path, \" > \")\n\t\t\t}\n\t\t\treturn []Chunk{{Title: title, Content: string(serialized)}}\n\t\t}\n\t\treturn nil\n\t}\n}\n\nfunc chunkJSONObject(obj map[string]any, path []string, maxBytes int) []Chunk {\n\t// Check if flat (no nested objects/arrays).\n\tflat := true\n\tfor _, v := range obj {\n\t\tswitch v.(type) {\n\t\tcase map[string]any, []any:\n\t\t\tflat = false\n\t\t}\n\t\tif !flat {\n\t\t\tbreak\n\t\t}\n\t}\n\n\tserialized, _ := json.MarshalIndent(obj, \"\", \"  \")\n\n\tif flat && len(serialized) < maxBytes {\n\t\ttitle := \"(root)\"\n\t\tif len(path) > 0 {\n\t\t\ttitle = strings.Join(path, \" > \")\n\t\t}\n\t\treturn []Chunk{{Title: title, Content: string(serialized), HasCode: true}}\n\t}\n\n\t// Recurse into each key in sorted order for deterministic output.\n\tvar chunks []Chunk\n\tfor _, key := range slices.Sorted(maps.Keys(obj)) {\n\t\tval := obj[key]\n\t\tchildPath := append(append([]string{}, path...), key)\n\t\tsub := walkJSON(val, childPath, maxBytes)\n\t\tif len(sub) == 0 {\n\t\t\t// Small primitive — emit inline.\n\t\t\ts, _ := json.Marshal(val)\n\t\t\ttitle := strings.Join(childPath, \" > \")\n\t\t\tchunks = append(chunks, Chunk{Title: title, Content: string(s), HasCode: true})\n\t\t} else {\n\t\t\tchunks = append(chunks, sub...)\n\t\t}\n\t}\n\treturn chunks\n}\n\nfunc chunkJSONArray(arr []any, prefix string, maxBytes int) []Chunk {\n\tif len(arr) == 0 {\n\t\treturn nil\n\t}\n\n\tidField := findIdentityField(arr)\n\tvar chunks []Chunk\n\tvar batch []any\n\tbatchSize := 0\n\tstartIdx := 0\n\n\tflushBatch := func(endIdx int) {\n\t\tif len(batch) == 0 {\n\t\t\treturn\n\t\t}\n\t\tserialized, _ := json.MarshalIndent(batch, \"\", \"  \")\n\t\ttitle := jsonBatchTitle(prefix, batch, idField, startIdx, endIdx)\n\t\tchunks = append(chunks, Chunk{Title: title, Content: string(serialized), HasCode: true})\n\t}\n\n\tfor i, item := range arr {\n\t\ts, _ := json.Marshal(item)\n\t\titemSize := len(s)\n\n\t\tif batchSize > 0 && batchSize+itemSize > maxBytes && len(batch) > 0 {\n\t\t\tflushBatch(startIdx + len(batch) - 1)\n\t\t\tbatch = nil\n\t\t\tbatchSize = 0\n\t\t\tstartIdx = i\n\t\t}\n\n\t\tbatch = append(batch, item)\n\t\tbatchSize += itemSize\n\t}\n\tflushBatch(startIdx + len(batch) - 1)\n\n\treturn chunks\n}\n\nfunc findIdentityField(arr []any) string {\n\tif len(arr) == 0 {\n\t\treturn \"\"\n\t}\n\tobj, ok := arr[0].(map[string]any)\n\tif !ok {\n\t\treturn \"\"\n\t}\n\tcandidates := []string{\"id\", \"name\", \"title\", \"path\", \"slug\", \"key\", \"label\"}\n\tfor _, field := range candidates {\n\t\tif v, exists := obj[field]; exists {\n\t\t\tswitch v.(type) {\n\t\t\tcase string, float64, int:\n\t\t\t\treturn field\n\t\t\t}\n\t\t}\n\t}\n\treturn \"\"\n}\n\nfunc jsonBatchTitle(prefix string, batch []any, idField string, startIdx, endIdx int) string {\n\tif idField != \"\" {\n\t\tids := extractIDs(batch, idField)\n\t\tswitch len(ids) {\n\t\tcase 1:\n\t\t\treturn fmt.Sprintf(\"%s > %s\", prefix, ids[0])\n\t\tcase 2, 3:\n\t\t\treturn fmt.Sprintf(\"%s > %s\", prefix, strings.Join(ids, \", \"))\n\t\tdefault:\n\t\t\tif len(ids) > 0 {\n\t\t\t\treturn fmt.Sprintf(\"%s > %s…%s\", prefix, ids[0], ids[len(ids)-1])\n\t\t\t}\n\t\t}\n\t}\n\tif startIdx == endIdx {\n\t\treturn fmt.Sprintf(\"%s > [%d]\", prefix, startIdx)\n\t}\n\treturn fmt.Sprintf(\"%s > [%d-%d]\", prefix, startIdx, endIdx)\n}\n\nfunc extractIDs(batch []any, field string) []string {\n\tvar ids []string\n\tfor _, item := range batch {\n\t\tif obj, ok := item.(map[string]any); ok {\n\t\t\tif v, exists := obj[field]; exists {\n\t\t\t\tids = append(ids, fmt.Sprintf(\"%v\", v))\n\t\t\t}\n\t\t}\n\t}\n\treturn ids\n}\n","numLines":401,"startLine":1,"totalLines":401}},"sourceToolAssistantUUID":"32fc8f19-12a7-47db-8191-6e7b03d5068d","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"e073a3fd-f903-4c84-a672-8cb4dd71639e","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0122k4CQdttrSaVgDwfurWDF","type":"tool_result","content":"1\tpackage store\n2\t\n3\timport (\n4\t\t\"crypto/sha256\"\n5\t\t\"database/sql\"\n6\t\t\"encoding/hex\"\n7\t\t\"encoding/json\"\n8\t\t\"fmt\"\n9\t\t\"log/slog\"\n10\t\n11\t\t\"github.com/serpro69/capy/internal/sanitize\"\n12\t)\n13\t\n14\t// Index indexes content into the knowledge base. It auto-detects\n15\t// content type if contentType is empty. Duplicate content (same label\n16\t// and hash) is skipped; changed content replaces the old source.\n17\t// kind must be a valid SourceKind (KindDurable or KindEphemeral).\n18\tfunc (s *ContentStore) Index(content, label, contentType string, kind SourceKind) (*IndexResult, error) {\n19\t\tdb, err := s.getDB()\n20\t\tif err != nil {\n21\t\t\treturn nil, err\n22\t\t}\n23\t\n24\t\tif !kind.Valid() {\n25\t\t\treturn nil, fmt.Errorf(\"invalid source kind %q\", kind)\n26\t\t}\n27\t\n28\t\tif contentType == \"\" {\n29\t\t\tcontentType = DetectContentType(content)\n30\t\t}\n31\t\n32\t\t// Strip secrets before hashing so that re-indexing with new patterns\n33\t\t// produces a different hash and triggers an update.\n34\t\tcontent = sanitize.StripSecrets(content)\n35\t\n36\t\thash := contentHash(content)\n37\t\n38\t\t// Chunk content before entering the transaction to minimize lock hold time.\n39\t\tchunks := chunkContent(content, contentType)\n40\t\tcodeChunks := 0\n41\t\tfor i := range chunks {\n42\t\t\tif chunks[i].HasCode {\n43\t\t\t\tcodeChunks++\n44\t\t\t\tchunks[i].ContentType = \"code\"\n45\t\t\t} else {\n46\t\t\t\tchunks[i].ContentType = \"prose\"\n47\t\t\t}\n48\t\t}\n49\t\n50\t\t// Acquire SQLite's RESERVED write lock for the whole transaction so the\n51\t\t// dedup SELECT and the INSERT/UPDATE that follows cannot interleave with\n52\t\t// another writer. database/sql's Begin() issues BEGIN DEFERRED, which\n53\t\t// only takes the write lock on the first write statement — we force that\n54\t\t// by executing a no-op DELETE right after opening the tx. Same idiom\n55\t\t// used by migrate.go's beginImmediate.\n56\t\ttx, err := db.BeginTx(s.ctx(), &sql.TxOptions{})\n57\t\tif err != nil {\n58\t\t\treturn nil, fmt.Errorf(\"beginning transaction: %w\", err)\n59\t\t}\n60\t\tdefer tx.Rollback()\n61\t\n62\t\tif _, err := tx.Exec(\"DELETE FROM sources WHERE 0\"); err != nil {\n63\t\t\treturn nil, fmt.Errorf(\"acquiring write lock: %w\", err)\n64\t\t}\n65\t\n66\t\t// Check for existing source with same label (inside transaction).\n67\t\tvar existingID int64\n68\t\tvar existingHash sql.NullString\n69\t\tvar existingKind SourceKind\n70\t\terr = tx.Stmt(s.stmtFindSourceByLabel).QueryRow(label).Scan(&existingID, &existingHash, &existingKind)\n71\t\tif err == nil {\n72\t\t\tif existingHash.Valid && existingHash.String == hash {\n73\t\t\t\t// Same content — promote/demote kind if needed, update access time.\n74\t\t\t\t// stmtUpdateSourceKind already sets last_accessed_at, so only\n75\t\t\t\t// call stmtUpdateSourceAccess when kind is unchanged.\n76\t\t\t\tif existingKind != kind {\n77\t\t\t\t\tif _, err := tx.Stmt(s.stmtUpdateSourceKind).Exec(kind, existingID); err != nil {\n78\t\t\t\t\t\treturn nil, fmt.Errorf(\"updating source kind: %w\", err)\n79\t\t\t\t\t}\n80\t\t\t\t} else {\n81\t\t\t\t\tif _, err := tx.Stmt(s.stmtUpdateSourceAccess).Exec(label, hash); err != nil {\n82\t\t\t\t\t\treturn nil, fmt.Errorf(\"updating access time: %w\", err)\n83\t\t\t\t\t}\n84\t\t\t\t}\n85\t\t\t\tif err := tx.Commit(); err != nil {\n86\t\t\t\t\treturn nil, fmt.Errorf(\"committing transaction: %w\", err)\n87\t\t\t\t}\n88\t\t\t\treturn &IndexResult{\n89\t\t\t\t\tSourceID:       existingID,\n90\t\t\t\t\tLabel:          label,\n91\t\t\t\t\tKind:           kind,\n92\t\t\t\t\tAlreadyIndexed: true,\n93\t\t\t\t}, nil\n94\t\t\t}\n95\t\t\t// Different content — delete old source + chunks.\n96\t\t\tif err := s.deleteSourceTx(tx, existingID); err != nil {\n97\t\t\t\treturn nil, fmt.Errorf(\"deleting old source: %w\", err)\n98\t\t\t}\n99\t\t}\n100\t\n101\t\t// Insert source and chunks.\n102\t\tres, err := tx.Stmt(s.stmtInsertSource).Exec(label, contentType, len(chunks), codeChunks, hash, kind)\n103\t\tif err != nil {\n104\t\t\treturn nil, fmt.Errorf(\"inserting source: %w\", err)\n105\t\t}\n106\t\tsourceID, _ := res.LastInsertId()\n107\t\n108\t\tstmtChunk := tx.Stmt(s.stmtInsertChunk)\n109\t\tstmtTrigram := tx.Stmt(s.stmtInsertTrigram)\n110\t\tfor _, c := range chunks {\n111\t\t\tif _, err := stmtChunk.Exec(c.Title, c.Content, sourceID, c.ContentType); err != nil {\n112\t\t\t\treturn nil, fmt.Errorf(\"inserting chunk: %w\", err)\n113\t\t\t}\n114\t\t\tif _, err := stmtTrigram.Exec(c.Title, c.Content, sourceID, c.ContentType); err != nil {\n115\t\t\t\treturn nil, fmt.Errorf(\"inserting trigram chunk: %w\", err)\n116\t\t\t}\n117\t\t}\n118\t\n119\t\tif err := tx.Commit(); err != nil {\n120\t\t\treturn nil, fmt.Errorf(\"committing transaction: %w\", err)\n121\t\t}\n122\t\n123\t\tafter := s.insertCount.Add(int64(len(chunks)))\n124\t\tif after >= optimizeEvery {\n125\t\t\tif s.insertCount.CompareAndSwap(after, 0) {\n126\t\t\t\ts.optimizeFTS(db)\n127\t\t\t}\n128\t\t}\n129\t\n130\t\t// Extract vocabulary outside the main transaction.\n131\t\tif err := s.extractAndStoreVocabulary(content); err != nil {\n132\t\t\tslog.Warn(\"vocabulary extraction failed\", \"label\", label, \"error\", err)\n133\t\t}\n134\t\n135\t\treturn &IndexResult{\n136\t\t\tSourceID:    sourceID,\n137\t\t\tLabel:       label,\n138\t\t\tTotalChunks: len(chunks),\n139\t\t\tCodeChunks:  codeChunks,\n140\t\t\tContentType: contentType,\n141\t\t\tKind:        kind,\n142\t\t}, nil\n143\t}\n144\t\n145\t// IndexPlainText is a convenience entry point that forces plaintext chunking.\n146\tfunc (s *ContentStore) IndexPlainText(content, label string, kind SourceKind) (*IndexResult, error) {\n147\t\treturn s.Index(content, label, \"plaintext\", kind)\n148\t}\n149\t\n150\t// IndexJSON is a convenience entry point that forces JSON chunking.\n151\tfunc (s *ContentStore) IndexJSON(content, label string, kind SourceKind) (*IndexResult, error) {\n152\t\treturn s.Index(content, label, \"json\", kind)\n153\t}\n154\t\n155\tfunc chunkContent(content, contentType string) []Chunk {\n156\t\tvar chunks []Chunk\n157\t\tswitch contentType {\n158\t\tcase \"markdown\":\n159\t\t\tchunks = chunkMarkdown(content, maxChunkBytes)\n160\t\tcase \"json\":\n161\t\t\tchunks = chunkJSON(content, maxChunkBytes)\n162\t\tdefault:\n163\t\t\tchunks = chunkPlainText(content, 20)\n164\t\t}\n165\t\tif len(chunks) == 0 {\n166\t\t\tchunks = []Chunk{{Title: \"Content\", Content: content}}\n167\t\t}\n168\t\treturn chunks\n169\t}\n170\t\n171\tfunc (s *ContentStore) deleteSourceTx(tx *sql.Tx, sourceID int64) error {\n172\t\tif _, err := tx.Stmt(s.stmtDeleteChunksBySource).Exec(sourceID); err != nil {\n173\t\t\treturn err\n174\t\t}\n175\t\tif _, err := tx.Stmt(s.stmtDeleteTrigramBySource).Exec(sourceID); err != nil {\n176\t\t\treturn err\n177\t\t}\n178\t\tif _, err := tx.Stmt(s.stmtDeleteSource).Exec(sourceID); err != nil {\n179\t\t\treturn err\n180\t\t}\n181\t\treturn nil\n182\t}\n183\t\n184\t// chunkJSON parses JSON and chunks it. Falls back to plaintext on parse error.\n185\tfunc chunkJSON(content string, maxBytes int) []Chunk {\n186\t\tvar parsed any\n187\t\tif err := jsonUnmarshal([]byte(content), &parsed); err != nil {\n188\t\t\treturn chunkPlainText(content, 20)\n189\t\t}\n190\t\tchunks := walkJSON(parsed, nil, maxBytes)\n191\t\tif len(chunks) == 0 {\n192\t\t\treturn chunkPlainText(content, 20)\n193\t\t}\n194\t\treturn chunks\n195\t}\n196\t\n197\tfunc contentHash(content string) string {\n198\t\th := sha256.Sum256([]byte(content))\n199\t\treturn hex.EncodeToString(h[:])\n200\t}\n201\t\n202\t// jsonUnmarshal wraps json.Unmarshal.\n203\tvar jsonUnmarshal = json.Unmarshal\n204\t"}]},"uuid":"0f72bb61-a506-4a06-8a64-a6d675cf70e5","timestamp":"2026-04-23T18:44:11.294Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/index.go","content":"package store\n\nimport (\n\t\"crypto/sha256\"\n\t\"database/sql\"\n\t\"encoding/hex\"\n\t\"encoding/json\"\n\t\"fmt\"\n\t\"log/slog\"\n\n\t\"github.com/serpro69/capy/internal/sanitize\"\n)\n\n// Index indexes content into the knowledge base. It auto-detects\n// content type if contentType is empty. Duplicate content (same label\n// and hash) is skipped; changed content replaces the old source.\n// kind must be a valid SourceKind (KindDurable or KindEphemeral).\nfunc (s *ContentStore) Index(content, label, contentType string, kind SourceKind) (*IndexResult, error) {\n\tdb, err := s.getDB()\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif !kind.Valid() {\n\t\treturn nil, fmt.Errorf(\"invalid source kind %q\", kind)\n\t}\n\n\tif contentType == \"\" {\n\t\tcontentType = DetectContentType(content)\n\t}\n\n\t// Strip secrets before hashing so that re-indexing with new patterns\n\t// produces a different hash and triggers an update.\n\tcontent = sanitize.StripSecrets(content)\n\n\thash := contentHash(content)\n\n\t// Chunk content before entering the transaction to minimize lock hold time.\n\tchunks := chunkContent(content, contentType)\n\tcodeChunks := 0\n\tfor i := range chunks {\n\t\tif chunks[i].HasCode {\n\t\t\tcodeChunks++\n\t\t\tchunks[i].ContentType = \"code\"\n\t\t} else {\n\t\t\tchunks[i].ContentType = \"prose\"\n\t\t}\n\t}\n\n\t// Acquire SQLite's RESERVED write lock for the whole transaction so the\n\t// dedup SELECT and the INSERT/UPDATE that follows cannot interleave with\n\t// another writer. database/sql's Begin() issues BEGIN DEFERRED, which\n\t// only takes the write lock on the first write statement — we force that\n\t// by executing a no-op DELETE right after opening the tx. Same idiom\n\t// used by migrate.go's beginImmediate.\n\ttx, err := db.BeginTx(s.ctx(), &sql.TxOptions{})\n\tif err != nil {\n\t\treturn nil, fmt.Errorf(\"beginning transaction: %w\", err)\n\t}\n\tdefer tx.Rollback()\n\n\tif _, err := tx.Exec(\"DELETE FROM sources WHERE 0\"); err != nil {\n\t\treturn nil, fmt.Errorf(\"acquiring write lock: %w\", err)\n\t}\n\n\t// Check for existing source with same label (inside transaction).\n\tvar existingID int64\n\tvar existingHash sql.NullString\n\tvar existingKind SourceKind\n\terr = tx.Stmt(s.stmtFindSourceByLabel).QueryRow(label).Scan(&existingID, &existingHash, &existingKind)\n\tif err == nil {\n\t\tif existingHash.Valid && existingHash.String == hash {\n\t\t\t// Same content — promote/demote kind if needed, update access time.\n\t\t\t// stmtUpdateSourceKind already sets last_accessed_at, so only\n\t\t\t// call stmtUpdateSourceAccess when kind is unchanged.\n\t\t\tif existingKind != kind {\n\t\t\t\tif _, err := tx.Stmt(s.stmtUpdateSourceKind).Exec(kind, existingID); err != nil {\n\t\t\t\t\treturn nil, fmt.Errorf(\"updating source kind: %w\", err)\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\tif _, err := tx.Stmt(s.stmtUpdateSourceAccess).Exec(label, hash); err != nil {\n\t\t\t\t\treturn nil, fmt.Errorf(\"updating access time: %w\", err)\n\t\t\t\t}\n\t\t\t}\n\t\t\tif err := tx.Commit(); err != nil {\n\t\t\t\treturn nil, fmt.Errorf(\"committing transaction: %w\", err)\n\t\t\t}\n\t\t\treturn &IndexResult{\n\t\t\t\tSourceID:       existingID,\n\t\t\t\tLabel:          label,\n\t\t\t\tKind:           kind,\n\t\t\t\tAlreadyIndexed: true,\n\t\t\t}, nil\n\t\t}\n\t\t// Different content — delete old source + chunks.\n\t\tif err := s.deleteSourceTx(tx, existingID); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"deleting old source: %w\", err)\n\t\t}\n\t}\n\n\t// Insert source and chunks.\n\tres, err := tx.Stmt(s.stmtInsertSource).Exec(label, contentType, len(chunks), codeChunks, hash, kind)\n\tif err != nil {\n\t\treturn nil, fmt.Errorf(\"inserting source: %w\", err)\n\t}\n\tsourceID, _ := res.LastInsertId()\n\n\tstmtChunk := tx.Stmt(s.stmtInsertChunk)\n\tstmtTrigram := tx.Stmt(s.stmtInsertTrigram)\n\tfor _, c := range chunks {\n\t\tif _, err := stmtChunk.Exec(c.Title, c.Content, sourceID, c.ContentType); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"inserting chunk: %w\", err)\n\t\t}\n\t\tif _, err := stmtTrigram.Exec(c.Title, c.Content, sourceID, c.ContentType); err != nil {\n\t\t\treturn nil, fmt.Errorf(\"inserting trigram chunk: %w\", err)\n\t\t}\n\t}\n\n\tif err := tx.Commit(); err != nil {\n\t\treturn nil, fmt.Errorf(\"committing transaction: %w\", err)\n\t}\n\n\tafter := s.insertCount.Add(int64(len(chunks)))\n\tif after >= optimizeEvery {\n\t\tif s.insertCount.CompareAndSwap(after, 0) {\n\t\t\ts.optimizeFTS(db)\n\t\t}\n\t}\n\n\t// Extract vocabulary outside the main transaction.\n\tif err := s.extractAndStoreVocabulary(content); err != nil {\n\t\tslog.Warn(\"vocabulary extraction failed\", \"label\", label, \"error\", err)\n\t}\n\n\treturn &IndexResult{\n\t\tSourceID:    sourceID,\n\t\tLabel:       label,\n\t\tTotalChunks: len(chunks),\n\t\tCodeChunks:  codeChunks,\n\t\tContentType: contentType,\n\t\tKind:        kind,\n\t}, nil\n}\n\n// IndexPlainText is a convenience entry point that forces plaintext chunking.\nfunc (s *ContentStore) IndexPlainText(content, label string, kind SourceKind) (*IndexResult, error) {\n\treturn s.Index(content, label, \"plaintext\", kind)\n}\n\n// IndexJSON is a convenience entry point that forces JSON chunking.\nfunc (s *ContentStore) IndexJSON(content, label string, kind SourceKind) (*IndexResult, error) {\n\treturn s.Index(content, label, \"json\", kind)\n}\n\nfunc chunkContent(content, contentType string) []Chunk {\n\tvar chunks []Chunk\n\tswitch contentType {\n\tcase \"markdown\":\n\t\tchunks = chunkMarkdown(content, maxChunkBytes)\n\tcase \"json\":\n\t\tchunks = chunkJSON(content, maxChunkBytes)\n\tdefault:\n\t\tchunks = chunkPlainText(content, 20)\n\t}\n\tif len(chunks) == 0 {\n\t\tchunks = []Chunk{{Title: \"Content\", Content: content}}\n\t}\n\treturn chunks\n}\n\nfunc (s *ContentStore) deleteSourceTx(tx *sql.Tx, sourceID int64) error {\n\tif _, err := tx.Stmt(s.stmtDeleteChunksBySource).Exec(sourceID); err != nil {\n\t\treturn err\n\t}\n\tif _, err := tx.Stmt(s.stmtDeleteTrigramBySource).Exec(sourceID); err != nil {\n\t\treturn err\n\t}\n\tif _, err := tx.Stmt(s.stmtDeleteSource).Exec(sourceID); err != nil {\n\t\treturn err\n\t}\n\treturn nil\n}\n\n// chunkJSON parses JSON and chunks it. Falls back to plaintext on parse error.\nfunc chunkJSON(content string, maxBytes int) []Chunk {\n\tvar parsed any\n\tif err := jsonUnmarshal([]byte(content), &parsed); err != nil {\n\t\treturn chunkPlainText(content, 20)\n\t}\n\tchunks := walkJSON(parsed, nil, maxBytes)\n\tif len(chunks) == 0 {\n\t\treturn chunkPlainText(content, 20)\n\t}\n\treturn chunks\n}\n\nfunc contentHash(content string) string {\n\th := sha256.Sum256([]byte(content))\n\treturn hex.EncodeToString(h[:])\n}\n\n// jsonUnmarshal wraps json.Unmarshal.\nvar jsonUnmarshal = json.Unmarshal\n","numLines":204,"startLine":1,"totalLines":204}},"sourceToolAssistantUUID":"e073a3fd-f903-4c84-a672-8cb4dd71639e","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"12f84ea5-faa0-49c3-ac76-9598e6ad95ff","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BgoN1YBxb1FSjvDxaSfDuo","type":"tool_result","content":"1\tpackage store\n2\t\n3\timport (\n4\t\t\"fmt\"\n5\t\t\"log/slog\"\n6\t\t\"math\"\n7\t\t\"os\"\n8\t\t\"time\"\n9\t)\n10\t\n11\tconst (\n12\t\tlambdaDecay = 0.045 // temporal decay rate\n13\t\tsigmaAccess = 0.3   // weight of recency boost\n14\t\n15\t\thotThreshold       = 0.7\n16\t\twarmThreshold      = 0.4\n17\t\tcoldThreshold      = 0.15\n18\t\tevictableThreshold = coldThreshold // sources below coldThreshold are evictable\n19\t)\n20\t\n21\t// retentionScore computes a continuous retention score for a source.\n22\t// Formula: salience × exp(-λ × daysSinceIndexed) + σ × recencyBoost\n23\t// where salience = baseSalience(contentType) + frequencyBonus(accessCount)\n24\tfunc retentionScore(src SourceInfo, now time.Time) float64 {\n25\t\t// Base salience by content type.\n26\t\tvar salience float64\n27\t\tswitch {\n28\t\tcase src.CodeChunkCount > 0 && src.CodeChunkCount == src.ChunkCount:\n29\t\t\tsalience = 0.7 // pure code\n30\t\tcase src.CodeChunkCount > 0:\n31\t\t\tsalience = 0.6 // mixed\n32\t\tdefault:\n33\t\t\tsalience = 0.5 // prose\n34\t\t}\n35\t\n36\t\t// Frequency bonus: min(0.2, accessCount × 0.02) — folds into salience,\n37\t\t// so it decays with age just like the base content-type weight.\n38\t\tfrequencyBonus := math.Min(0.2, float64(src.AccessCount)*0.02)\n39\t\tsalience += frequencyBonus\n40\t\n41\t\t// Temporal decay.\n42\t\tdaysSinceIndexed := now.Sub(src.IndexedAt).Hours() / 24\n43\t\tif daysSinceIndexed < 0 {\n44\t\t\tdaysSinceIndexed = 0\n45\t\t}\n46\t\ttemporalDecay := math.Exp(-lambdaDecay * daysSinceIndexed)\n47\t\n48\t\t// Recency boost: 1 / (1 + daysSinceLastAccess), or 0 if never accessed.\n49\t\t// Guarded by AccessCount > 0 because the schema sets last_accessed_at to\n50\t\t// CURRENT_TIMESTAMP on insert — IsZero() alone would always be true.\n51\t\tvar recencyBoost float64\n52\t\tif src.AccessCount > 0 && !src.LastAccessedAt.IsZero() {\n53\t\t\tdaysSinceLastAccess := now.Sub(src.LastAccessedAt).Hours() / 24\n54\t\t\tif daysSinceLastAccess < 0 {\n55\t\t\t\tdaysSinceLastAccess = 0\n56\t\t\t}\n57\t\t\trecencyBoost = 1.0 / (1.0 + daysSinceLastAccess)\n58\t\t}\n59\t\n60\t\treturn salience*temporalDecay + sigmaAccess*recencyBoost\n61\t}\n62\t\n63\t// classifyTier maps a SourceInfo to a tier string based on retention score.\n64\tfunc classifyTier(src SourceInfo, now time.Time) (string, float64) {\n65\t\tscore := retentionScore(src, now)\n66\t\tswitch {\n67\t\tcase score >= hotThreshold:\n68\t\t\treturn \"hot\", score\n69\t\tcase score >= warmThreshold:\n70\t\t\treturn \"warm\", score\n71\t\tcase score >= coldThreshold:\n72\t\t\treturn \"cold\", score\n73\t\tdefault:\n74\t\t\treturn \"evictable\", score\n75\t\t}\n76\t}\n77\t\n78\t// ClassifySources returns all sources with tier classification.\n79\t//\n80\t// Durable rows get retention-score-based tiers (hot/warm/cold/evictable,\n81\t// see classifyTier). Ephemeral rows are bucketed by age against\n82\t// ephemeralTTL: \"fresh\" when indexed within the TTL window, \"stale\" when\n83\t// past it and awaiting the next Cleanup() sweep. RetentionScore is left\n84\t// at 0 for ephemeral rows — retention math is meaningless for TTL-lived\n85\t// content. Non-positive ephemeralTTL falls back to the safe 24h default,\n86\t// matching cleanupEphemeral.\n87\tfunc (s *ContentStore) ClassifySources(ephemeralTTL time.Duration) ([]SourceInfo, error) {\n88\t\tsources, err := s.ListSources()\n89\t\tif err != nil {\n90\t\t\treturn nil, err\n91\t\t}\n92\t\n93\t\tif ephemeralTTL <= 0 {\n94\t\t\tephemeralTTL = 24 * time.Hour\n95\t\t}\n96\t\tnow := time.Now()\n97\t\tttlCutoff := now.Add(-ephemeralTTL)\n98\t\n99\t\tfor i := range sources {\n100\t\t\tif sources[i].Kind == KindEphemeral {\n101\t\t\t\tif sources[i].IndexedAt.Before(ttlCutoff) {\n102\t\t\t\t\tsources[i].Tier = \"stale\"\n103\t\t\t\t} else {\n104\t\t\t\t\tsources[i].Tier = \"fresh\"\n105\t\t\t\t}\n106\t\t\t\tcontinue\n107\t\t\t}\n108\t\t\tsources[i].Tier, sources[i].RetentionScore = classifyTier(sources[i], now)\n109\t\t}\n110\t\treturn sources, nil\n111\t}\n112\t\n113\t// Cleanup removes sources via two independent paths:\n114\t//   - durable: retention-score-based eviction (ADR-011) for `kind = 'durable'`.\n115\t//   - ephemeral: strict TTL eviction for `kind = 'ephemeral'` — ignores\n116\t//     access_count so intent-search hits don't extend lifetime (ADR-017).\n117\t//\n118\t// If dryRun is true, returns what would be removed without deleting.\n119\t// The returned slice tags each SourceInfo with EvictionReason (\"retention\"\n120\t// or \"ttl\") so callers can render per-kind breakdowns.\n121\t// Vocabulary is shared and never deleted.\n122\tfunc (s *ContentStore) Cleanup(dryRun bool, ephemeralTTL time.Duration) ([]SourceInfo, error) {\n123\t\tdurable, err := s.cleanupDurable(dryRun, ephemeralTTL)\n124\t\tif err != nil {\n125\t\t\treturn nil, err\n126\t\t}\n127\t\tephemeral, err := s.cleanupEphemeral(dryRun, ephemeralTTL)\n128\t\tif err != nil {\n129\t\t\treturn nil, err\n130\t\t}\n131\t\n132\t\tmerged := make([]SourceInfo, 0, len(durable)+len(ephemeral))\n133\t\tmerged = append(merged, durable...)\n134\t\tmerged = append(merged, ephemeral...)\n135\t\treturn merged, nil\n136\t}\n137\t\n138\t// PurgeEphemeral evicts ephemeral sources past the TTL window, skipping\n139\t// durable retention entirely. Intended for a one-shot \"clear scratch\"\n140\t// operation exposed via capy_cleanup's purge_ephemeral flag. Durable\n141\t// rows are never touched, regardless of retention score.\n142\tfunc (s *ContentStore) PurgeEphemeral(dryRun bool, ttl time.Duration) ([]SourceInfo, error) {\n143\t\treturn s.cleanupEphemeral(dryRun, ttl)\n144\t}\n145\t\n146\t// cleanupDurable applies retention-score-based eviction to durable sources.\n147\t// A source is a candidate iff its retentionScore is below the evictable\n148\t// threshold AND it has never been accessed. ephemeralTTL is threaded\n149\t// through only so ClassifySources can bucket ephemeral rows consistently;\n150\t// it does not influence durable eviction.\n151\tfunc (s *ContentStore) cleanupDurable(dryRun bool, ephemeralTTL time.Duration) ([]SourceInfo, error) {\n152\t\t// ClassifySources walks both kinds; the ephemeral branch is wasted\n153\t\t// work here but negligible at the corpus sizes this store targets.\n154\t\t// Keep the single entrypoint for consistency with Stats().\n155\t\tsources, err := s.ClassifySources(ephemeralTTL)\n156\t\tif err != nil {\n157\t\t\treturn nil, err\n158\t\t}\n159\t\n160\t\tvar candidates []SourceInfo\n161\t\tfor _, src := range sources {\n162\t\t\tif src.Kind != KindDurable {\n163\t\t\t\tcontinue\n164\t\t\t}\n165\t\t\tif src.RetentionScore >= evictableThreshold {\n166\t\t\t\tcontinue\n167\t\t\t}\n168\t\t\tif src.AccessCount > 0 {\n169\t\t\t\tcontinue\n170\t\t\t}\n171\t\t\tsrc.EvictionReason = \"retention\"\n172\t\t\tcandidates = append(candidates, src)\n173\t\t}\n174\t\n175\t\treturn candidates, s.evict(candidates, dryRun)\n176\t}\n177\t\n178\t// cleanupEphemeral evicts ephemeral sources whose indexed_at is older than\n179\t// ttl. access_count is intentionally ignored — intent-search writes must not\n180\t// extend ephemeral lifetime (ADR-017). Non-positive ttl is treated as the\n181\t// safe default of 24 h. Every returned SourceInfo carries\n182\t// EvictionReason = \"ttl\" — the stamping lives here so Cleanup and\n183\t// PurgeEphemeral don't each have to remember to tag.\n184\tfunc (s *ContentStore) cleanupEphemeral(dryRun bool, ttl time.Duration) ([]SourceInfo, error) {\n185\t\tdb, err := s.getDB()\n186\t\tif err != nil {\n187\t\t\treturn nil, err\n188\t\t}\n189\t\n190\t\tif ttl <= 0 {\n191\t\t\tslog.Warn(\"cleanupEphemeral: non-positive TTL supplied, falling back to 24h\",\n192\t\t\t\t\"ttl\", ttl)\n193\t\t\tttl = 24 * time.Hour\n194\t\t}\n195\t\tcutoff := time.Now().Add(-ttl).UTC().Format(\"2006-01-02 15:04:05\")\n196\t\n197\t\trows, err := db.Query(`\n198\t\t\tSELECT id, label, content_type, chunk_count, code_chunk_count,\n199\t\t\t\tindexed_at, last_accessed_at, access_count, content_hash, kind\n200\t\t\tFROM sources\n201\t\t\tWHERE kind = ? AND indexed_at < ?\n202\t\t\tORDER BY id DESC`, KindEphemeral, cutoff)\n203\t\tif err != nil {\n204\t\t\treturn nil, fmt.Errorf(\"selecting stale ephemeral sources: %w\", err)\n205\t\t}\n206\t\tdefer rows.Close()\n207\t\n208\t\tvar candidates []SourceInfo\n209\t\tfor rows.Next() {\n210\t\t\tvar si SourceInfo\n211\t\t\tvar indexedAt, lastAccessedAt string\n212\t\t\tif err := rows.Scan(&si.ID, &si.Label, &si.ContentType, &si.ChunkCount,\n213\t\t\t\t&si.CodeChunkCount, &indexedAt, &lastAccessedAt, &si.AccessCount,\n214\t\t\t\t&si.ContentHash, &si.Kind); err != nil {\n215\t\t\t\tslog.Warn(\"cleanupEphemeral: row scan failed, skipping\", \"error\", err)\n216\t\t\t\tcontinue\n217\t\t\t}\n218\t\t\tsi.IndexedAt, _ = time.Parse(\"2006-01-02 15:04:05\", indexedAt)\n219\t\t\tsi.LastAccessedAt, _ = time.Parse(\"2006-01-02 15:04:05\", lastAccessedAt)\n220\t\t\tsi.EvictionReason = \"ttl\"\n221\t\t\tcandidates = append(candidates, si)\n222\t\t}\n223\t\tif err := rows.Err(); err != nil {\n224\t\t\treturn nil, err\n225\t\t}\n226\t\n227\t\treturn candidates, s.evict(candidates, dryRun)\n228\t}\n229\t\n230\t// evict performs the transactional delete for a list of candidates. On\n231\t// dryRun or an empty list it is a no-op. Safe to call from both cleanup\n232\t// paths — the three prepared statements are keyed by source id.\n233\tfunc (s *ContentStore) evict(candidates []SourceInfo, dryRun bool) error {\n234\t\tif dryRun || len(candidates) == 0 {\n235\t\t\treturn nil\n236\t\t}\n237\t\n238\t\tdb, err := s.getDB()\n239\t\tif err != nil {\n240\t\t\treturn err\n241\t\t}\n242\t\n243\t\t// Use beginImmediate so the eviction sweep gets the same retry-on-BUSY\n244\t\t// backoff as the migration and Index paths; a plain db.Begin() surfaces\n245\t\t// SQLITE_BUSY mid-transaction under write contention.\n246\t\ttx, err := beginImmediate(db)\n247\t\tif err != nil {\n248\t\t\treturn fmt.Errorf(\"beginning cleanup transaction: %w\", err)\n249\t\t}\n250\t\tdefer tx.Rollback() //nolint:errcheck // rollback after commit is a no-op\n251\t\n252\t\t// Bind the three prepared statements to the transaction once. Calling\n253\t\t// tx.Stmt inside the loop would allocate a fresh transaction-bound\n254\t\t// statement per candidate, which compounds on large eviction sweeps.\n255\t\tdelChunks := tx.Stmt(s.stmtDeleteChunksBySource)\n256\t\tdelTrigram := tx.Stmt(s.stmtDeleteTrigramBySource)\n257\t\tdelSource := tx.Stmt(s.stmtDeleteSource)\n258\t\n259\t\tfor _, src := range candidates {\n260\t\t\tif _, err := delChunks.Exec(src.ID); err != nil {\n261\t\t\t\treturn fmt.Errorf(\"deleting chunks for source %d: %w\", src.ID, err)\n262\t\t\t}\n263\t\t\tif _, err := delTrigram.Exec(src.ID); err != nil {\n264\t\t\t\treturn fmt.Errorf(\"deleting trigram chunks for source %d: %w\", src.ID, err)\n265\t\t\t}\n266\t\t\tif _, err := delSource.Exec(src.ID); err != nil {\n267\t\t\t\treturn fmt.Errorf(\"deleting source %d: %w\", src.ID, err)\n268\t\t\t}\n269\t\t}\n270\t\n271\t\tif err := tx.Commit(); err != nil {\n272\t\t\treturn fmt.Errorf(\"committing cleanup: %w\", err)\n273\t\t}\n274\t\treturn nil\n275\t}\n276\t\n277\t// Stats returns knowledge base statistics. ephemeralTTL is required to\n278\t// bucket ephemeral sources into fresh/stale — callers should pass the\n279\t// same TTL they use for Cleanup (typically\n280\t// `config.Store.Cleanup.EphemeralTTLHours`).\n281\tfunc (s *ContentStore) Stats(ephemeralTTL time.Duration) (*StoreStats, error) {\n282\t\tdb, err := s.getDB()\n283\t\tif err != nil {\n284\t\t\treturn nil, err\n285\t\t}\n286\t\n287\t\tvar stats StoreStats\n288\t\n289\t\tif err := db.QueryRow(\"SELECT COUNT(*) FROM sources\").Scan(&stats.SourceCount); err != nil {\n290\t\t\tslog.Warn(\"failed to count sources\", \"error\", err)\n291\t\t}\n292\t\tif err := db.QueryRow(\"SELECT COUNT(*) FROM chunks\").Scan(&stats.ChunkCount); err != nil {\n293\t\t\tslog.Warn(\"failed to count chunks\", \"error\", err)\n294\t\t}\n295\t\tif err := db.QueryRow(\"SELECT COUNT(*) FROM vocabulary\").Scan(&stats.VocabCount); err != nil {\n296\t\t\tslog.Warn(\"failed to count vocabulary\", \"error\", err)\n297\t\t}\n298\t\n299\t\t// DB file size.\n300\t\tif fi, err := os.Stat(s.dbPath); err == nil {\n301\t\t\tstats.DBSizeBytes = fi.Size()\n302\t\t}\n303\t\n304\t\t// Per-kind counts and durable tier / ephemeral fresh-stale distribution.\n305\t\tsources, err := s.ClassifySources(ephemeralTTL)\n306\t\tif err != nil {\n307\t\t\treturn &stats, nil\n308\t\t}\n309\t\tfor _, src := range sources {\n310\t\t\tif src.Kind == KindEphemeral {\n311\t\t\t\tstats.EphemeralSourceCount++\n312\t\t\t\tswitch src.Tier {\n313\t\t\t\tcase \"fresh\":\n314\t\t\t\t\tstats.EphemeralFreshCount++\n315\t\t\t\tcase \"stale\":\n316\t\t\t\t\tstats.EphemeralStaleCount++\n317\t\t\t\t}\n318\t\t\t\tcontinue\n319\t\t\t}\n320\t\t\tstats.DurableSourceCount++\n321\t\t\tswitch src.Tier {\n322\t\t\tcase \"hot\":\n323\t\t\t\tstats.DurableHotCount++\n324\t\t\tcase \"warm\":\n325\t\t\t\tstats.DurableWarmCount++\n326\t\t\tcase \"cold\":\n327\t\t\t\tstats.DurableColdCount++\n328\t\t\tcase \"evictable\":\n329\t\t\t\tstats.DurableEvictableCount++\n330\t\t\t}\n331\t\t}\n332\t\n333\t\treturn &stats, nil\n334\t}\n335\t"}]},"uuid":"fbe9f956-ad47-4b92-844b-570e95f35539","timestamp":"2026-04-23T18:44:11.294Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/cleanup.go","content":"package store\n\nimport (\n\t\"fmt\"\n\t\"log/slog\"\n\t\"math\"\n\t\"os\"\n\t\"time\"\n)\n\nconst (\n\tlambdaDecay = 0.045 // temporal decay rate\n\tsigmaAccess = 0.3   // weight of recency boost\n\n\thotThreshold       = 0.7\n\twarmThreshold      = 0.4\n\tcoldThreshold      = 0.15\n\tevictableThreshold = coldThreshold // sources below coldThreshold are evictable\n)\n\n// retentionScore computes a continuous retention score for a source.\n// Formula: salience × exp(-λ × daysSinceIndexed) + σ × recencyBoost\n// where salience = baseSalience(contentType) + frequencyBonus(accessCount)\nfunc retentionScore(src SourceInfo, now time.Time) float64 {\n\t// Base salience by content type.\n\tvar salience float64\n\tswitch {\n\tcase src.CodeChunkCount > 0 && src.CodeChunkCount == src.ChunkCount:\n\t\tsalience = 0.7 // pure code\n\tcase src.CodeChunkCount > 0:\n\t\tsalience = 0.6 // mixed\n\tdefault:\n\t\tsalience = 0.5 // prose\n\t}\n\n\t// Frequency bonus: min(0.2, accessCount × 0.02) — folds into salience,\n\t// so it decays with age just like the base content-type weight.\n\tfrequencyBonus := math.Min(0.2, float64(src.AccessCount)*0.02)\n\tsalience += frequencyBonus\n\n\t// Temporal decay.\n\tdaysSinceIndexed := now.Sub(src.IndexedAt).Hours() / 24\n\tif daysSinceIndexed < 0 {\n\t\tdaysSinceIndexed = 0\n\t}\n\ttemporalDecay := math.Exp(-lambdaDecay * daysSinceIndexed)\n\n\t// Recency boost: 1 / (1 + daysSinceLastAccess), or 0 if never accessed.\n\t// Guarded by AccessCount > 0 because the schema sets last_accessed_at to\n\t// CURRENT_TIMESTAMP on insert — IsZero() alone would always be true.\n\tvar recencyBoost float64\n\tif src.AccessCount > 0 && !src.LastAccessedAt.IsZero() {\n\t\tdaysSinceLastAccess := now.Sub(src.LastAccessedAt).Hours() / 24\n\t\tif daysSinceLastAccess < 0 {\n\t\t\tdaysSinceLastAccess = 0\n\t\t}\n\t\trecencyBoost = 1.0 / (1.0 + daysSinceLastAccess)\n\t}\n\n\treturn salience*temporalDecay + sigmaAccess*recencyBoost\n}\n\n// classifyTier maps a SourceInfo to a tier string based on retention score.\nfunc classifyTier(src SourceInfo, now time.Time) (string, float64) {\n\tscore := retentionScore(src, now)\n\tswitch {\n\tcase score >= hotThreshold:\n\t\treturn \"hot\", score\n\tcase score >= warmThreshold:\n\t\treturn \"warm\", score\n\tcase score >= coldThreshold:\n\t\treturn \"cold\", score\n\tdefault:\n\t\treturn \"evictable\", score\n\t}\n}\n\n// ClassifySources returns all sources with tier classification.\n//\n// Durable rows get retention-score-based tiers (hot/warm/cold/evictable,\n// see classifyTier). Ephemeral rows are bucketed by age against\n// ephemeralTTL: \"fresh\" when indexed within the TTL window, \"stale\" when\n// past it and awaiting the next Cleanup() sweep. RetentionScore is left\n// at 0 for ephemeral rows — retention math is meaningless for TTL-lived\n// content. Non-positive ephemeralTTL falls back to the safe 24h default,\n// matching cleanupEphemeral.\nfunc (s *ContentStore) ClassifySources(ephemeralTTL time.Duration) ([]SourceInfo, error) {\n\tsources, err := s.ListSources()\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif ephemeralTTL <= 0 {\n\t\tephemeralTTL = 24 * time.Hour\n\t}\n\tnow := time.Now()\n\tttlCutoff := now.Add(-ephemeralTTL)\n\n\tfor i := range sources {\n\t\tif sources[i].Kind == KindEphemeral {\n\t\t\tif sources[i].IndexedAt.Before(ttlCutoff) {\n\t\t\t\tsources[i].Tier = \"stale\"\n\t\t\t} else {\n\t\t\t\tsources[i].Tier = \"fresh\"\n\t\t\t}\n\t\t\tcontinue\n\t\t}\n\t\tsources[i].Tier, sources[i].RetentionScore = classifyTier(sources[i], now)\n\t}\n\treturn sources, nil\n}\n\n// Cleanup removes sources via two independent paths:\n//   - durable: retention-score-based eviction (ADR-011) for `kind = 'durable'`.\n//   - ephemeral: strict TTL eviction for `kind = 'ephemeral'` — ignores\n//     access_count so intent-search hits don't extend lifetime (ADR-017).\n//\n// If dryRun is true, returns what would be removed without deleting.\n// The returned slice tags each SourceInfo with EvictionReason (\"retention\"\n// or \"ttl\") so callers can render per-kind breakdowns.\n// Vocabulary is shared and never deleted.\nfunc (s *ContentStore) Cleanup(dryRun bool, ephemeralTTL time.Duration) ([]SourceInfo, error) {\n\tdurable, err := s.cleanupDurable(dryRun, ephemeralTTL)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\tephemeral, err := s.cleanupEphemeral(dryRun, ephemeralTTL)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tmerged := make([]SourceInfo, 0, len(durable)+len(ephemeral))\n\tmerged = append(merged, durable...)\n\tmerged = append(merged, ephemeral...)\n\treturn merged, nil\n}\n\n// PurgeEphemeral evicts ephemeral sources past the TTL window, skipping\n// durable retention entirely. Intended for a one-shot \"clear scratch\"\n// operation exposed via capy_cleanup's purge_ephemeral flag. Durable\n// rows are never touched, regardless of retention score.\nfunc (s *ContentStore) PurgeEphemeral(dryRun bool, ttl time.Duration) ([]SourceInfo, error) {\n\treturn s.cleanupEphemeral(dryRun, ttl)\n}\n\n// cleanupDurable applies retention-score-based eviction to durable sources.\n// A source is a candidate iff its retentionScore is below the evictable\n// threshold AND it has never been accessed. ephemeralTTL is threaded\n// through only so ClassifySources can bucket ephemeral rows consistently;\n// it does not influence durable eviction.\nfunc (s *ContentStore) cleanupDurable(dryRun bool, ephemeralTTL time.Duration) ([]SourceInfo, error) {\n\t// ClassifySources walks both kinds; the ephemeral branch is wasted\n\t// work here but negligible at the corpus sizes this store targets.\n\t// Keep the single entrypoint for consistency with Stats().\n\tsources, err := s.ClassifySources(ephemeralTTL)\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tvar candidates []SourceInfo\n\tfor _, src := range sources {\n\t\tif src.Kind != KindDurable {\n\t\t\tcontinue\n\t\t}\n\t\tif src.RetentionScore >= evictableThreshold {\n\t\t\tcontinue\n\t\t}\n\t\tif src.AccessCount > 0 {\n\t\t\tcontinue\n\t\t}\n\t\tsrc.EvictionReason = \"retention\"\n\t\tcandidates = append(candidates, src)\n\t}\n\n\treturn candidates, s.evict(candidates, dryRun)\n}\n\n// cleanupEphemeral evicts ephemeral sources whose indexed_at is older than\n// ttl. access_count is intentionally ignored — intent-search writes must not\n// extend ephemeral lifetime (ADR-017). Non-positive ttl is treated as the\n// safe default of 24 h. Every returned SourceInfo carries\n// EvictionReason = \"ttl\" — the stamping lives here so Cleanup and\n// PurgeEphemeral don't each have to remember to tag.\nfunc (s *ContentStore) cleanupEphemeral(dryRun bool, ttl time.Duration) ([]SourceInfo, error) {\n\tdb, err := s.getDB()\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tif ttl <= 0 {\n\t\tslog.Warn(\"cleanupEphemeral: non-positive TTL supplied, falling back to 24h\",\n\t\t\t\"ttl\", ttl)\n\t\tttl = 24 * time.Hour\n\t}\n\tcutoff := time.Now().Add(-ttl).UTC().Format(\"2006-01-02 15:04:05\")\n\n\trows, err := db.Query(`\n\t\tSELECT id, label, content_type, chunk_count, code_chunk_count,\n\t\t\tindexed_at, last_accessed_at, access_count, content_hash, kind\n\t\tFROM sources\n\t\tWHERE kind = ? AND indexed_at < ?\n\t\tORDER BY id DESC`, KindEphemeral, cutoff)\n\tif err != nil {\n\t\treturn nil, fmt.Errorf(\"selecting stale ephemeral sources: %w\", err)\n\t}\n\tdefer rows.Close()\n\n\tvar candidates []SourceInfo\n\tfor rows.Next() {\n\t\tvar si SourceInfo\n\t\tvar indexedAt, lastAccessedAt string\n\t\tif err := rows.Scan(&si.ID, &si.Label, &si.ContentType, &si.ChunkCount,\n\t\t\t&si.CodeChunkCount, &indexedAt, &lastAccessedAt, &si.AccessCount,\n\t\t\t&si.ContentHash, &si.Kind); err != nil {\n\t\t\tslog.Warn(\"cleanupEphemeral: row scan failed, skipping\", \"error\", err)\n\t\t\tcontinue\n\t\t}\n\t\tsi.IndexedAt, _ = time.Parse(\"2006-01-02 15:04:05\", indexedAt)\n\t\tsi.LastAccessedAt, _ = time.Parse(\"2006-01-02 15:04:05\", lastAccessedAt)\n\t\tsi.EvictionReason = \"ttl\"\n\t\tcandidates = append(candidates, si)\n\t}\n\tif err := rows.Err(); err != nil {\n\t\treturn nil, err\n\t}\n\n\treturn candidates, s.evict(candidates, dryRun)\n}\n\n// evict performs the transactional delete for a list of candidates. On\n// dryRun or an empty list it is a no-op. Safe to call from both cleanup\n// paths — the three prepared statements are keyed by source id.\nfunc (s *ContentStore) evict(candidates []SourceInfo, dryRun bool) error {\n\tif dryRun || len(candidates) == 0 {\n\t\treturn nil\n\t}\n\n\tdb, err := s.getDB()\n\tif err != nil {\n\t\treturn err\n\t}\n\n\t// Use beginImmediate so the eviction sweep gets the same retry-on-BUSY\n\t// backoff as the migration and Index paths; a plain db.Begin() surfaces\n\t// SQLITE_BUSY mid-transaction under write contention.\n\ttx, err := beginImmediate(db)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"beginning cleanup transaction: %w\", err)\n\t}\n\tdefer tx.Rollback() //nolint:errcheck // rollback after commit is a no-op\n\n\t// Bind the three prepared statements to the transaction once. Calling\n\t// tx.Stmt inside the loop would allocate a fresh transaction-bound\n\t// statement per candidate, which compounds on large eviction sweeps.\n\tdelChunks := tx.Stmt(s.stmtDeleteChunksBySource)\n\tdelTrigram := tx.Stmt(s.stmtDeleteTrigramBySource)\n\tdelSource := tx.Stmt(s.stmtDeleteSource)\n\n\tfor _, src := range candidates {\n\t\tif _, err := delChunks.Exec(src.ID); err != nil {\n\t\t\treturn fmt.Errorf(\"deleting chunks for source %d: %w\", src.ID, err)\n\t\t}\n\t\tif _, err := delTrigram.Exec(src.ID); err != nil {\n\t\t\treturn fmt.Errorf(\"deleting trigram chunks for source %d: %w\", src.ID, err)\n\t\t}\n\t\tif _, err := delSource.Exec(src.ID); err != nil {\n\t\t\treturn fmt.Errorf(\"deleting source %d: %w\", src.ID, err)\n\t\t}\n\t}\n\n\tif err := tx.Commit(); err != nil {\n\t\treturn fmt.Errorf(\"committing cleanup: %w\", err)\n\t}\n\treturn nil\n}\n\n// Stats returns knowledge base statistics. ephemeralTTL is required to\n// bucket ephemeral sources into fresh/stale — callers should pass the\n// same TTL they use for Cleanup (typically\n// `config.Store.Cleanup.EphemeralTTLHours`).\nfunc (s *ContentStore) Stats(ephemeralTTL time.Duration) (*StoreStats, error) {\n\tdb, err := s.getDB()\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\tvar stats StoreStats\n\n\tif err := db.QueryRow(\"SELECT COUNT(*) FROM sources\").Scan(&stats.SourceCount); err != nil {\n\t\tslog.Warn(\"failed to count sources\", \"error\", err)\n\t}\n\tif err := db.QueryRow(\"SELECT COUNT(*) FROM chunks\").Scan(&stats.ChunkCount); err != nil {\n\t\tslog.Warn(\"failed to count chunks\", \"error\", err)\n\t}\n\tif err := db.QueryRow(\"SELECT COUNT(*) FROM vocabulary\").Scan(&stats.VocabCount); err != nil {\n\t\tslog.Warn(\"failed to count vocabulary\", \"error\", err)\n\t}\n\n\t// DB file size.\n\tif fi, err := os.Stat(s.dbPath); err == nil {\n\t\tstats.DBSizeBytes = fi.Size()\n\t}\n\n\t// Per-kind counts and durable tier / ephemeral fresh-stale distribution.\n\tsources, err := s.ClassifySources(ephemeralTTL)\n\tif err != nil {\n\t\treturn &stats, nil\n\t}\n\tfor _, src := range sources {\n\t\tif src.Kind == KindEphemeral {\n\t\t\tstats.EphemeralSourceCount++\n\t\t\tswitch src.Tier {\n\t\t\tcase \"fresh\":\n\t\t\t\tstats.EphemeralFreshCount++\n\t\t\tcase \"stale\":\n\t\t\t\tstats.EphemeralStaleCount++\n\t\t\t}\n\t\t\tcontinue\n\t\t}\n\t\tstats.DurableSourceCount++\n\t\tswitch src.Tier {\n\t\tcase \"hot\":\n\t\t\tstats.DurableHotCount++\n\t\tcase \"warm\":\n\t\t\tstats.DurableWarmCount++\n\t\tcase \"cold\":\n\t\t\tstats.DurableColdCount++\n\t\tcase \"evictable\":\n\t\t\tstats.DurableEvictableCount++\n\t\t}\n\t}\n\n\treturn &stats, nil\n}\n","numLines":335,"startLine":1,"totalLines":335}},"sourceToolAssistantUUID":"12f84ea5-faa0-49c3-ac76-9598e6ad95ff","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"8f891537-6dfc-4a18-822d-9015052f93b0","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TXuMUEK28u2zmjMLSMHrwi","type":"tool_result","content":"1\tpackage store\n2\t\n3\timport \"time\"\n4\t\n5\t// SourceKind classifies a source's lifecycle for search filtering and cleanup.\n6\ttype SourceKind string\n7\t\n8\tconst (\n9\t\tKindDurable   SourceKind = \"durable\"\n10\t\tKindEphemeral SourceKind = \"ephemeral\"\n11\t)\n12\t\n13\t// Valid reports whether k is a recognized source kind.\n14\tfunc (k SourceKind) Valid() bool {\n15\t\treturn k == KindDurable || k == KindEphemeral\n16\t}\n17\t\n18\t// Chunk represents a unit of indexed content.\n19\ttype Chunk struct {\n20\t\tTitle       string\n21\t\tContent     string\n22\t\tHasCode     bool\n23\t\tContentType string // \"code\" or \"prose\"\n24\t}\n25\t\n26\t// SearchOptions controls filtering for search queries.\n27\ttype SearchOptions struct {\n28\t\tSource          string       // partial match filter (LIKE '%source%')\n29\t\tContentType     string       // \"code\", \"prose\", or \"\" (no filter) — internal only, not in MCP schema\n30\t\tSourceMatchMode string       // \"like\" (default) or \"exact\"\n31\t\tMaxPerSource    int          // per-source result cap for diversification; 0 = default (2)\n32\t\tIncludeKinds    []SourceKind // empty = default (durable only); ignored when Source != \"\"\n33\t}\n34\t\n35\t// SearchResult is a single result from a search query.\n36\ttype SearchResult struct {\n37\t\tLabel       string\n38\t\tTitle       string\n39\t\tContent     string\n40\t\tSourceID    int64\n41\t\tContentType string\n42\t\tHighlighted string\n43\t\tRank        float64\n44\t\tFusedScore  float64\n45\t\tMatchLayer  string\n46\t}\n47\t\n48\t// SourceInfo describes an indexed source.\n49\ttype SourceInfo struct {\n50\t\tID             int64\n51\t\tLabel          string\n52\t\tContentType    string\n53\t\tChunkCount     int\n54\t\tCodeChunkCount int\n55\t\tIndexedAt      time.Time\n56\t\tLastAccessedAt time.Time\n57\t\tAccessCount    int\n58\t\tContentHash    string\n59\t\tKind           SourceKind\n60\t\tTier           string  // \"hot\", \"warm\", \"cold\", \"evictable\"\n61\t\tRetentionScore float64 // computed at query time from salience, decay, and access boost\n62\t\tEvictionReason string  // \"retention\" or \"ttl\" — populated only by Cleanup results\n63\t}\n64\t\n65\t// StoreStats contains knowledge base statistics.\n66\ttype StoreStats struct {\n67\t\tSourceCount int\n68\t\tChunkCount  int\n69\t\tVocabCount  int\n70\t\tDBSizeBytes int64\n71\t\n72\t\t// Per-kind source counts.\n73\t\tDurableSourceCount   int\n74\t\tEphemeralSourceCount int\n75\t\n76\t\t// Durable retention tiers — renamed from Hot/Warm/Cold/EvictableCount\n77\t\t// to reflect that retention scoring applies only to durable rows.\n78\t\tDurableHotCount       int\n79\t\tDurableWarmCount      int\n80\t\tDurableColdCount      int\n81\t\tDurableEvictableCount int\n82\t\n83\t\t// Ephemeral TTL buckets. fresh = indexed within TTL; stale = past TTL\n84\t\t// and awaiting the next Cleanup() sweep.\n85\t\tEphemeralFreshCount int\n86\t\tEphemeralStaleCount int\n87\t}\n88\t\n89\t// SourceMeta is lightweight metadata for a single source (used by TTL cache).\n90\ttype SourceMeta struct {\n91\t\tLabel      string\n92\t\tChunkCount int\n93\t\tIndexedAt  time.Time\n94\t\tKind       SourceKind\n95\t}\n96\t\n97\t// IndexResult is returned after indexing content.\n98\ttype IndexResult struct {\n99\t\tSourceID       int64\n100\t\tLabel          string\n101\t\tTotalChunks    int\n102\t\tCodeChunks     int\n103\t\tContentType    string\n104\t\tKind           SourceKind\n105\t\tAlreadyIndexed bool\n106\t}\n107\t"}]},"uuid":"a5bcb441-8529-4350-9492-2de78588019b","timestamp":"2026-04-23T18:44:11.295Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/types.go","content":"package store\n\nimport \"time\"\n\n// SourceKind classifies a source's lifecycle for search filtering and cleanup.\ntype SourceKind string\n\nconst (\n\tKindDurable   SourceKind = \"durable\"\n\tKindEphemeral SourceKind = \"ephemeral\"\n)\n\n// Valid reports whether k is a recognized source kind.\nfunc (k SourceKind) Valid() bool {\n\treturn k == KindDurable || k == KindEphemeral\n}\n\n// Chunk represents a unit of indexed content.\ntype Chunk struct {\n\tTitle       string\n\tContent     string\n\tHasCode     bool\n\tContentType string // \"code\" or \"prose\"\n}\n\n// SearchOptions controls filtering for search queries.\ntype SearchOptions struct {\n\tSource          string       // partial match filter (LIKE '%source%')\n\tContentType     string       // \"code\", \"prose\", or \"\" (no filter) — internal only, not in MCP schema\n\tSourceMatchMode string       // \"like\" (default) or \"exact\"\n\tMaxPerSource    int          // per-source result cap for diversification; 0 = default (2)\n\tIncludeKinds    []SourceKind // empty = default (durable only); ignored when Source != \"\"\n}\n\n// SearchResult is a single result from a search query.\ntype SearchResult struct {\n\tLabel       string\n\tTitle       string\n\tContent     string\n\tSourceID    int64\n\tContentType string\n\tHighlighted string\n\tRank        float64\n\tFusedScore  float64\n\tMatchLayer  string\n}\n\n// SourceInfo describes an indexed source.\ntype SourceInfo struct {\n\tID             int64\n\tLabel          string\n\tContentType    string\n\tChunkCount     int\n\tCodeChunkCount int\n\tIndexedAt      time.Time\n\tLastAccessedAt time.Time\n\tAccessCount    int\n\tContentHash    string\n\tKind           SourceKind\n\tTier           string  // \"hot\", \"warm\", \"cold\", \"evictable\"\n\tRetentionScore float64 // computed at query time from salience, decay, and access boost\n\tEvictionReason string  // \"retention\" or \"ttl\" — populated only by Cleanup results\n}\n\n// StoreStats contains knowledge base statistics.\ntype StoreStats struct {\n\tSourceCount int\n\tChunkCount  int\n\tVocabCount  int\n\tDBSizeBytes int64\n\n\t// Per-kind source counts.\n\tDurableSourceCount   int\n\tEphemeralSourceCount int\n\n\t// Durable retention tiers — renamed from Hot/Warm/Cold/EvictableCount\n\t// to reflect that retention scoring applies only to durable rows.\n\tDurableHotCount       int\n\tDurableWarmCount      int\n\tDurableColdCount      int\n\tDurableEvictableCount int\n\n\t// Ephemeral TTL buckets. fresh = indexed within TTL; stale = past TTL\n\t// and awaiting the next Cleanup() sweep.\n\tEphemeralFreshCount int\n\tEphemeralStaleCount int\n}\n\n// SourceMeta is lightweight metadata for a single source (used by TTL cache).\ntype SourceMeta struct {\n\tLabel      string\n\tChunkCount int\n\tIndexedAt  time.Time\n\tKind       SourceKind\n}\n\n// IndexResult is returned after indexing content.\ntype IndexResult struct {\n\tSourceID       int64\n\tLabel          string\n\tTotalChunks    int\n\tCodeChunks     int\n\tContentType    string\n\tKind           SourceKind\n\tAlreadyIndexed bool\n}\n","numLines":107,"startLine":1,"totalLines":107}},"sourceToolAssistantUUID":"8f891537-6dfc-4a18-822d-9015052f93b0","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"093f43e5-e310-4b2a-856d-faeaf89d57cd","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0195YR2PBrve9jZrsEBdh9id","type":"tool_result","content":"1\tpackage store\n2\t\n3\tconst schemaSQL = `\n4\tPRAGMA journal_mode = WAL;\n5\tPRAGMA synchronous = NORMAL;\n6\tPRAGMA busy_timeout = 5000;\n7\tPRAGMA foreign_keys = ON;\n8\t\n9\tCREATE TABLE IF NOT EXISTS sources (\n10\t  id INTEGER PRIMARY KEY AUTOINCREMENT,\n11\t  label TEXT NOT NULL,\n12\t  content_type TEXT NOT NULL DEFAULT 'plaintext',\n13\t  chunk_count INTEGER NOT NULL DEFAULT 0,\n14\t  code_chunk_count INTEGER NOT NULL DEFAULT 0,\n15\t  indexed_at TEXT DEFAULT CURRENT_TIMESTAMP,\n16\t  last_accessed_at TEXT DEFAULT CURRENT_TIMESTAMP,\n17\t  access_count INTEGER NOT NULL DEFAULT 0,\n18\t  content_hash TEXT,\n19\t  kind TEXT NOT NULL DEFAULT 'durable' CHECK (kind IN ('ephemeral', 'durable'))\n20\t);\n21\t\n22\tCREATE VIRTUAL TABLE IF NOT EXISTS chunks USING fts5(\n23\t  title,\n24\t  content,\n25\t  source_id UNINDEXED,\n26\t  content_type UNINDEXED,\n27\t  tokenize='porter unicode61'\n28\t);\n29\t\n30\tCREATE VIRTUAL TABLE IF NOT EXISTS chunks_trigram USING fts5(\n31\t  title,\n32\t  content,\n33\t  source_id UNINDEXED,\n34\t  content_type UNINDEXED,\n35\t  tokenize='trigram'\n36\t);\n37\t\n38\tCREATE TABLE IF NOT EXISTS vocabulary (\n39\t  word TEXT PRIMARY KEY\n40\t);\n41\t`\n42\t"}]},"uuid":"8b1b4553-1e01-4a7e-bf6e-16e881e3aa3a","timestamp":"2026-04-23T18:44:11.295Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/schema.go","content":"package store\n\nconst schemaSQL = `\nPRAGMA journal_mode = WAL;\nPRAGMA synchronous = NORMAL;\nPRAGMA busy_timeout = 5000;\nPRAGMA foreign_keys = ON;\n\nCREATE TABLE IF NOT EXISTS sources (\n  id INTEGER PRIMARY KEY AUTOINCREMENT,\n  label TEXT NOT NULL,\n  content_type TEXT NOT NULL DEFAULT 'plaintext',\n  chunk_count INTEGER NOT NULL DEFAULT 0,\n  code_chunk_count INTEGER NOT NULL DEFAULT 0,\n  indexed_at TEXT DEFAULT CURRENT_TIMESTAMP,\n  last_accessed_at TEXT DEFAULT CURRENT_TIMESTAMP,\n  access_count INTEGER NOT NULL DEFAULT 0,\n  content_hash TEXT,\n  kind TEXT NOT NULL DEFAULT 'durable' CHECK (kind IN ('ephemeral', 'durable'))\n);\n\nCREATE VIRTUAL TABLE IF NOT EXISTS chunks USING fts5(\n  title,\n  content,\n  source_id UNINDEXED,\n  content_type UNINDEXED,\n  tokenize='porter unicode61'\n);\n\nCREATE VIRTUAL TABLE IF NOT EXISTS chunks_trigram USING fts5(\n  title,\n  content,\n  source_id UNINDEXED,\n  content_type UNINDEXED,\n  tokenize='trigram'\n);\n\nCREATE TABLE IF NOT EXISTS vocabulary (\n  word TEXT PRIMARY KEY\n);\n`\n","numLines":42,"startLine":1,"totalLines":42}},"sourceToolAssistantUUID":"093f43e5-e310-4b2a-856d-faeaf89d57cd","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"e60c7dfa-189a-4120-96ef-ef66340f564e","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01UZWqP8XcUDGfByMxMwq8do","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01UyzJ1AFpskRoZdN3n7rB3Z","name":"Read","input":{"file_path":"/home/sergio/Projects/personal/capy/internal/config/paths.go"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10795,"cache_creation_input_tokens":3405,"cache_read_input_tokens":47577,"output_tokens":288,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3405,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCNqYDe9pzUnkMbCzBQ","type":"assistant","uuid":"1b2d5d75-c4f0-4903-a196-7af3a0c4e758","timestamp":"2026-04-23T18:44:16.423Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"c824d796-54fb-4e4c-97bf-28d1e5f8b423","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01V8uH9gbTMC6T6qq614Fpaf","type":"tool_result","content":"1\tpackage server\n2\t\n3\timport (\n4\t\t\"context\"\n5\t\t\"fmt\"\n6\t\t\"log\"\n7\t\t\"os\"\n8\t\t\"sync\"\n9\t\t\"time\"\n10\t\n11\t\t\"github.com/mark3labs/mcp-go/mcp\"\n12\t\tmcpserver \"github.com/mark3labs/mcp-go/server\"\n13\t\t\"github.com/serpro69/capy/internal/config\"\n14\t\t\"github.com/serpro69/capy/internal/executor\"\n15\t\t\"github.com/serpro69/capy/internal/security\"\n16\t\t\"github.com/serpro69/capy/internal/store\"\n17\t\t\"github.com/serpro69/capy/internal/version\"\n18\t)\n19\t\n20\t// searchThrottle tracks progressive search throttling per session.\n21\ttype searchThrottle struct {\n22\t\tmu          sync.Mutex\n23\t\tcount       int\n24\t\twindowStart time.Time\n25\t}\n26\t\n27\t// advance increments the call count and returns the new count and window age.\n28\t// If the window has expired, it resets the window atomically before incrementing.\n29\t// Combined into a single lock acquisition to avoid TOCTOU between separate\n30\t// increment/age/reset calls.\n31\tfunc (t *searchThrottle) advance(window time.Duration) (int, time.Duration) {\n32\t\tt.mu.Lock()\n33\t\tdefer t.mu.Unlock()\n34\t\n35\t\tage := time.Since(t.windowStart)\n36\t\tif age > window {\n37\t\t\tt.count = 0\n38\t\t\tt.windowStart = time.Now()\n39\t\t\tage = 0\n40\t\t}\n41\t\tt.count++\n42\t\treturn t.count, age\n43\t}\n44\t\n45\t// Server is the capy MCP server.\n46\ttype Server struct {\n47\t\tmcpServer      *mcpserver.MCPServer\n48\t\tstore          *store.ContentStore\n49\t\texecutor       *executor.PolyglotExecutor\n50\t\tsecurity       []security.SecurityPolicy\n51\t\treadDenyGlobs  [][]string // cached Read deny patterns\n52\t\tconfig         *config.Config\n53\t\tstats          *SessionStats\n54\t\tthrottle       *searchThrottle\n55\t\tstoreMu        sync.Once\n56\t\tprojectDir     string\n57\t}\n58\t\n59\t// NewServer creates a new Server. The store is lazily initialized on first use.\n60\tfunc NewServer(\n61\t\tcfg *config.Config,\n62\t\tpolicies []security.SecurityPolicy,\n63\t\texec *executor.PolyglotExecutor,\n64\t\tprojectDir string,\n65\t) *Server {\n66\t\treturn &Server{\n67\t\t\tconfig:        cfg,\n68\t\t\tsecurity:      policies,\n69\t\t\treadDenyGlobs: security.ReadToolDenyPatterns(\"Read\", projectDir, \"\"),\n70\t\t\texecutor:      exec,\n71\t\t\tstats:         NewSessionStats(),\n72\t\t\tthrottle:      &searchThrottle{windowStart: time.Now()},\n73\t\t\tprojectDir:    projectDir,\n74\t\t}\n75\t}\n76\t\n77\t// getStore returns the lazily-initialized ContentStore.\n78\tfunc (s *Server) getStore() *store.ContentStore {\n79\t\ts.storeMu.Do(func() {\n80\t\t\tdbPath := s.config.ResolveDBPath(s.projectDir)\n81\t\t\ts.store = store.NewContentStore(dbPath, s.projectDir, s.config.Store.TitleWeight)\n82\t\t})\n83\t\treturn s.store\n84\t}\n85\t\n86\t// ephemeralTTL resolves the ephemeral-source TTL from config with a\n87\t// safe 24h fallback. The loader rejects EphemeralTTLHours < 1 so the\n88\t// non-positive branch should be unreachable in production, but we guard\n89\t// it anyway for defense-in-depth — a 0 would cascade into cleanup.go's\n90\t// non-positive-TTL branch and log a warning on every Stats/Cleanup call.\n91\t// Also covers test paths that construct a Server without a config.\n92\tfunc (s *Server) ephemeralTTL() time.Duration {\n93\t\tif s.config == nil || s.config.Store.Cleanup.EphemeralTTLHours <= 0 {\n94\t\t\treturn 24 * time.Hour\n95\t\t}\n96\t\treturn time.Duration(s.config.Store.Cleanup.EphemeralTTLHours) * time.Hour\n97\t}\n98\t\n99\t// Serve starts the MCP server on stdio and blocks until shutdown.\n100\tfunc (s *Server) Serve(ctx context.Context) error {\n101\t\t// Unhandled panic recovery\n102\t\tdefer func() {\n103\t\t\tif r := recover(); r != nil {\n104\t\t\t\tfmt.Fprintf(os.Stderr, \"capy: unhandled panic: %v\\n\", r)\n105\t\t\t}\n106\t\t}()\n107\t\n108\t\ts.mcpServer = mcpserver.NewMCPServer(\n109\t\t\t\"capy\",\n110\t\t\tversion.Version,\n111\t\t\tmcpserver.WithToolCapabilities(false),\n112\t\t)\n113\t\n114\t\ts.registerTools()\n115\t\n116\t\t// Ensure cleanup runs on all exit paths (normal return, signals, parent death).\n117\t\tdefer s.shutdown()\n118\t\n119\t\t// Lifecycle guard: shutdown on parent death or signals\n120\t\tstopGuard := StartLifecycleGuard(func() {\n121\t\t\ts.shutdown()\n122\t\t\tos.Exit(0)\n123\t\t})\n124\t\tdefer stopGuard()\n125\t\n126\t\tstdio := mcpserver.NewStdioServer(s.mcpServer)\n127\t\tstdio.SetErrorLogger(log.New(os.Stderr, \"capy: \", log.LstdFlags))\n128\t\treturn stdio.Listen(ctx, os.Stdin, os.Stdout)\n129\t}\n130\t\n131\t// shutdown cleans up resources.\n132\tfunc (s *Server) shutdown() {\n133\t\tif s.executor != nil {\n134\t\t\ts.executor.CleanupBackgrounded()\n135\t\t}\n136\t\tif s.store != nil {\n137\t\t\t_ = s.store.Close()\n138\t\t}\n139\t}\n140\t\n141\t// registerToolsForTest is a test helper that only creates the MCP server\n142\t// and registers tools, without starting stdio transport.\n143\tfunc (s *Server) registerToolsForTest() {\n144\t\ts.mcpServer = mcpserver.NewMCPServer(\n145\t\t\t\"capy\",\n146\t\t\tversion.Version,\n147\t\t\tmcpserver.WithToolCapabilities(false),\n148\t\t)\n149\t\ts.registerTools()\n150\t}\n151\t\n152\t// textResult is a convenience helper for tool handlers.\n153\tfunc textResult(text string) *mcp.CallToolResult {\n154\t\treturn mcp.NewToolResultText(text)\n155\t}\n156\t\n157\t// errorResult is a convenience helper for tool handlers returning errors.\n158\tfunc errorResult(text string) *mcp.CallToolResult {\n159\t\treturn mcp.NewToolResultError(text)\n160\t}\n161\t"}]},"uuid":"0b51b008-6ece-4c2b-bd7b-9f14b155d5bf","timestamp":"2026-04-23T18:44:16.460Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/server/server.go","content":"package server\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"log\"\n\t\"os\"\n\t\"sync\"\n\t\"time\"\n\n\t\"github.com/mark3labs/mcp-go/mcp\"\n\tmcpserver \"github.com/mark3labs/mcp-go/server\"\n\t\"github.com/serpro69/capy/internal/config\"\n\t\"github.com/serpro69/capy/internal/executor\"\n\t\"github.com/serpro69/capy/internal/security\"\n\t\"github.com/serpro69/capy/internal/store\"\n\t\"github.com/serpro69/capy/internal/version\"\n)\n\n// searchThrottle tracks progressive search throttling per session.\ntype searchThrottle struct {\n\tmu          sync.Mutex\n\tcount       int\n\twindowStart time.Time\n}\n\n// advance increments the call count and returns the new count and window age.\n// If the window has expired, it resets the window atomically before incrementing.\n// Combined into a single lock acquisition to avoid TOCTOU between separate\n// increment/age/reset calls.\nfunc (t *searchThrottle) advance(window time.Duration) (int, time.Duration) {\n\tt.mu.Lock()\n\tdefer t.mu.Unlock()\n\n\tage := time.Since(t.windowStart)\n\tif age > window {\n\t\tt.count = 0\n\t\tt.windowStart = time.Now()\n\t\tage = 0\n\t}\n\tt.count++\n\treturn t.count, age\n}\n\n// Server is the capy MCP server.\ntype Server struct {\n\tmcpServer      *mcpserver.MCPServer\n\tstore          *store.ContentStore\n\texecutor       *executor.PolyglotExecutor\n\tsecurity       []security.SecurityPolicy\n\treadDenyGlobs  [][]string // cached Read deny patterns\n\tconfig         *config.Config\n\tstats          *SessionStats\n\tthrottle       *searchThrottle\n\tstoreMu        sync.Once\n\tprojectDir     string\n}\n\n// NewServer creates a new Server. The store is lazily initialized on first use.\nfunc NewServer(\n\tcfg *config.Config,\n\tpolicies []security.SecurityPolicy,\n\texec *executor.PolyglotExecutor,\n\tprojectDir string,\n) *Server {\n\treturn &Server{\n\t\tconfig:        cfg,\n\t\tsecurity:      policies,\n\t\treadDenyGlobs: security.ReadToolDenyPatterns(\"Read\", projectDir, \"\"),\n\t\texecutor:      exec,\n\t\tstats:         NewSessionStats(),\n\t\tthrottle:      &searchThrottle{windowStart: time.Now()},\n\t\tprojectDir:    projectDir,\n\t}\n}\n\n// getStore returns the lazily-initialized ContentStore.\nfunc (s *Server) getStore() *store.ContentStore {\n\ts.storeMu.Do(func() {\n\t\tdbPath := s.config.ResolveDBPath(s.projectDir)\n\t\ts.store = store.NewContentStore(dbPath, s.projectDir, s.config.Store.TitleWeight)\n\t})\n\treturn s.store\n}\n\n// ephemeralTTL resolves the ephemeral-source TTL from config with a\n// safe 24h fallback. The loader rejects EphemeralTTLHours < 1 so the\n// non-positive branch should be unreachable in production, but we guard\n// it anyway for defense-in-depth — a 0 would cascade into cleanup.go's\n// non-positive-TTL branch and log a warning on every Stats/Cleanup call.\n// Also covers test paths that construct a Server without a config.\nfunc (s *Server) ephemeralTTL() time.Duration {\n\tif s.config == nil || s.config.Store.Cleanup.EphemeralTTLHours <= 0 {\n\t\treturn 24 * time.Hour\n\t}\n\treturn time.Duration(s.config.Store.Cleanup.EphemeralTTLHours) * time.Hour\n}\n\n// Serve starts the MCP server on stdio and blocks until shutdown.\nfunc (s *Server) Serve(ctx context.Context) error {\n\t// Unhandled panic recovery\n\tdefer func() {\n\t\tif r := recover(); r != nil {\n\t\t\tfmt.Fprintf(os.Stderr, \"capy: unhandled panic: %v\\n\", r)\n\t\t}\n\t}()\n\n\ts.mcpServer = mcpserver.NewMCPServer(\n\t\t\"capy\",\n\t\tversion.Version,\n\t\tmcpserver.WithToolCapabilities(false),\n\t)\n\n\ts.registerTools()\n\n\t// Ensure cleanup runs on all exit paths (normal return, signals, parent death).\n\tdefer s.shutdown()\n\n\t// Lifecycle guard: shutdown on parent death or signals\n\tstopGuard := StartLifecycleGuard(func() {\n\t\ts.shutdown()\n\t\tos.Exit(0)\n\t})\n\tdefer stopGuard()\n\n\tstdio := mcpserver.NewStdioServer(s.mcpServer)\n\tstdio.SetErrorLogger(log.New(os.Stderr, \"capy: \", log.LstdFlags))\n\treturn stdio.Listen(ctx, os.Stdin, os.Stdout)\n}\n\n// shutdown cleans up resources.\nfunc (s *Server) shutdown() {\n\tif s.executor != nil {\n\t\ts.executor.CleanupBackgrounded()\n\t}\n\tif s.store != nil {\n\t\t_ = s.store.Close()\n\t}\n}\n\n// registerToolsForTest is a test helper that only creates the MCP server\n// and registers tools, without starting stdio transport.\nfunc (s *Server) registerToolsForTest() {\n\ts.mcpServer = mcpserver.NewMCPServer(\n\t\t\"capy\",\n\t\tversion.Version,\n\t\tmcpserver.WithToolCapabilities(false),\n\t)\n\ts.registerTools()\n}\n\n// textResult is a convenience helper for tool handlers.\nfunc textResult(text string) *mcp.CallToolResult {\n\treturn mcp.NewToolResultText(text)\n}\n\n// errorResult is a convenience helper for tool handlers returning errors.\nfunc errorResult(text string) *mcp.CallToolResult {\n\treturn mcp.NewToolResultError(text)\n}\n","numLines":161,"startLine":1,"totalLines":161}},"sourceToolAssistantUUID":"c824d796-54fb-4e4c-97bf-28d1e5f8b423","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"e60c7dfa-189a-4120-96ef-ef66340f564e","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011Y9Y4BkVvcGtfWHGThaxAP","type":"tool_result","content":"1\tpackage hook\n2\t\n3\timport (\n4\t\t\"fmt\"\n5\t\t\"io\"\n6\t\t\"os\"\n7\t\n8\t\t\"github.com/serpro69/capy/internal/adapter\"\n9\t\t\"github.com/serpro69/capy/internal/security\"\n10\t)\n11\t\n12\t// Run dispatches a hook event by reading JSON from stdin, routing to the\n13\t// appropriate handler, and writing the response JSON to stdout.\n14\tfunc Run(event string, a adapter.HookAdapter, policies []security.SecurityPolicy, projectDir string) error {\n15\t\tinput, err := io.ReadAll(os.Stdin)\n16\t\tif err != nil {\n17\t\t\treturn err\n18\t\t}\n19\t\n20\t\tvar output []byte\n21\t\tswitch event {\n22\t\tcase \"pretooluse\":\n23\t\t\toutput, err = handlePreToolUse(input, a, policies, projectDir)\n24\t\tcase \"posttooluse\":\n25\t\t\toutput, err = handlePostToolUse(input, a)\n26\t\tcase \"precompact\":\n27\t\t\toutput, err = handlePreCompact(input, a)\n28\t\tcase \"sessionstart\":\n29\t\t\toutput, err = handleSessionStart(input, a)\n30\t\tcase \"userpromptsubmit\":\n31\t\t\toutput, err = handleUserPromptSubmit(input, a)\n32\t\tcase \"sessionend\":\n33\t\t\thandleSessionEnd(projectDir)\n34\t\t\treturn nil // no output, no error — best effort\n35\t\tdefault:\n36\t\t\treturn fmt.Errorf(\"unknown hook event: %s\", event)\n37\t\t}\n38\t\n39\t\tif err != nil {\n40\t\t\treturn err\n41\t\t}\n42\t\tif output != nil {\n43\t\t\t_, err = os.Stdout.Write(output)\n44\t\t}\n45\t\treturn err\n46\t}\n47\t"}]},"uuid":"173d344e-ce6a-4029-a00c-62d7cca90dbe","timestamp":"2026-04-23T18:44:16.461Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/hook/hook.go","content":"package hook\n\nimport (\n\t\"fmt\"\n\t\"io\"\n\t\"os\"\n\n\t\"github.com/serpro69/capy/internal/adapter\"\n\t\"github.com/serpro69/capy/internal/security\"\n)\n\n// Run dispatches a hook event by reading JSON from stdin, routing to the\n// appropriate handler, and writing the response JSON to stdout.\nfunc Run(event string, a adapter.HookAdapter, policies []security.SecurityPolicy, projectDir string) error {\n\tinput, err := io.ReadAll(os.Stdin)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\tvar output []byte\n\tswitch event {\n\tcase \"pretooluse\":\n\t\toutput, err = handlePreToolUse(input, a, policies, projectDir)\n\tcase \"posttooluse\":\n\t\toutput, err = handlePostToolUse(input, a)\n\tcase \"precompact\":\n\t\toutput, err = handlePreCompact(input, a)\n\tcase \"sessionstart\":\n\t\toutput, err = handleSessionStart(input, a)\n\tcase \"userpromptsubmit\":\n\t\toutput, err = handleUserPromptSubmit(input, a)\n\tcase \"sessionend\":\n\t\thandleSessionEnd(projectDir)\n\t\treturn nil // no output, no error — best effort\n\tdefault:\n\t\treturn fmt.Errorf(\"unknown hook event: %s\", event)\n\t}\n\n\tif err != nil {\n\t\treturn err\n\t}\n\tif output != nil {\n\t\t_, err = os.Stdout.Write(output)\n\t}\n\treturn err\n}\n","numLines":47,"startLine":1,"totalLines":47}},"sourceToolAssistantUUID":"e60c7dfa-189a-4120-96ef-ef66340f564e","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"d5d4c8f9-5453-4a54-91df-1f0f0e826935","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XWShJcMV7p9n4wiXi66rCN","type":"tool_result","content":"1\tpackage server\n2\t\n3\timport (\n4\t\t\"os\"\n5\t\t\"os/signal\"\n6\t\t\"sync\"\n7\t\t\"syscall\"\n8\t\t\"time\"\n9\t)\n10\t\n11\t// StartLifecycleGuard monitors for parent process death and OS signals,\n12\t// calling onShutdown when the server should exit. Returns a cleanup function\n13\t// that must be called to stop the guard.\n14\tfunc StartLifecycleGuard(onShutdown func()) func() {\n15\t\toriginalPpid := os.Getppid()\n16\t\tvar once sync.Once\n17\t\n18\t\tshutdown := func() {\n19\t\t\tonce.Do(onShutdown)\n20\t\t}\n21\t\n22\t\t// Parent PID polling (every 30s) — detect orphaned server\n23\t\tticker := time.NewTicker(30 * time.Second)\n24\t\tgo func() {\n25\t\t\tfor range ticker.C {\n26\t\t\t\tppid := os.Getppid()\n27\t\t\t\tif ppid != originalPpid || ppid == 0 || ppid == 1 {\n28\t\t\t\t\tshutdown()\n29\t\t\t\t\treturn\n30\t\t\t\t}\n31\t\t\t}\n32\t\t}()\n33\t\n34\t\t// OS signals\n35\t\tsigCh := make(chan os.Signal, 1)\n36\t\tsignal.Notify(sigCh, syscall.SIGTERM, syscall.SIGINT, syscall.SIGHUP)\n37\t\tdone := make(chan struct{})\n38\t\tgo func() {\n39\t\t\tselect {\n40\t\t\tcase <-sigCh:\n41\t\t\t\tshutdown()\n42\t\t\tcase <-done:\n43\t\t\t}\n44\t\t}()\n45\t\n46\t\t// Return cleanup function\n47\t\treturn func() {\n48\t\t\tclose(done)\n49\t\t\tticker.Stop()\n50\t\t\tsignal.Stop(sigCh)\n51\t\t}\n52\t}\n53\t"}]},"uuid":"5b7444aa-2464-4907-90ab-b635e7143d82","timestamp":"2026-04-23T18:44:16.461Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/server/lifecycle.go","content":"package server\n\nimport (\n\t\"os\"\n\t\"os/signal\"\n\t\"sync\"\n\t\"syscall\"\n\t\"time\"\n)\n\n// StartLifecycleGuard monitors for parent process death and OS signals,\n// calling onShutdown when the server should exit. Returns a cleanup function\n// that must be called to stop the guard.\nfunc StartLifecycleGuard(onShutdown func()) func() {\n\toriginalPpid := os.Getppid()\n\tvar once sync.Once\n\n\tshutdown := func() {\n\t\tonce.Do(onShutdown)\n\t}\n\n\t// Parent PID polling (every 30s) — detect orphaned server\n\tticker := time.NewTicker(30 * time.Second)\n\tgo func() {\n\t\tfor range ticker.C {\n\t\t\tppid := os.Getppid()\n\t\t\tif ppid != originalPpid || ppid == 0 || ppid == 1 {\n\t\t\t\tshutdown()\n\t\t\t\treturn\n\t\t\t}\n\t\t}\n\t}()\n\n\t// OS signals\n\tsigCh := make(chan os.Signal, 1)\n\tsignal.Notify(sigCh, syscall.SIGTERM, syscall.SIGINT, syscall.SIGHUP)\n\tdone := make(chan struct{})\n\tgo func() {\n\t\tselect {\n\t\tcase <-sigCh:\n\t\t\tshutdown()\n\t\tcase <-done:\n\t\t}\n\t}()\n\n\t// Return cleanup function\n\treturn func() {\n\t\tclose(done)\n\t\tticker.Stop()\n\t\tsignal.Stop(sigCh)\n\t}\n}\n","numLines":53,"startLine":1,"totalLines":53}},"sourceToolAssistantUUID":"d5d4c8f9-5453-4a54-91df-1f0f0e826935","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"bdff7b5d-d902-460f-877b-1bc5b4a2380a","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DUz6wh2sjbtVi7abu9d4DU","type":"tool_result","content":"1\tpackage hook\n2\t\n3\timport \"github.com/serpro69/capy/internal/adapter\"\n4\t\n5\tfunc handleSessionStart(_ []byte, a adapter.HookAdapter) ([]byte, error) {\n6\t\treturn a.FormatSessionStart(RoutingBlock())\n7\t}\n8\t"}]},"uuid":"2c7afaea-e62b-4daf-946e-0968a8a57972","timestamp":"2026-04-23T18:44:16.461Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/hook/sessionstart.go","content":"package hook\n\nimport \"github.com/serpro69/capy/internal/adapter\"\n\nfunc handleSessionStart(_ []byte, a adapter.HookAdapter) ([]byte, error) {\n\treturn a.FormatSessionStart(RoutingBlock())\n}\n","numLines":8,"startLine":1,"totalLines":8}},"sourceToolAssistantUUID":"bdff7b5d-d902-460f-877b-1bc5b4a2380a","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"1b2d5d75-c4f0-4903-a196-7af3a0c4e758","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01UyzJ1AFpskRoZdN3n7rB3Z","type":"tool_result","content":"1\tpackage config\n2\t\n3\timport (\n4\t\t\"crypto/sha256\"\n5\t\t\"encoding/hex\"\n6\t\t\"os\"\n7\t\t\"os/exec\"\n8\t\t\"path/filepath\"\n9\t)\n10\t\n11\t// DetectProjectRoot finds the project root directory using:\n12\t//  1. CLAUDE_PROJECT_DIR env var\n13\t//  2. git rev-parse --show-toplevel\n14\t//  3. Walk up from cwd looking for .git/, .capy.toml, .capy/\n15\t//  4. Fallback: cwd\n16\tfunc DetectProjectRoot() string {\n17\t\tif dir := os.Getenv(\"CLAUDE_PROJECT_DIR\"); dir != \"\" {\n18\t\t\treturn dir\n19\t\t}\n20\t\n21\t\tif out, err := exec.Command(\"git\", \"rev-parse\", \"--show-toplevel\").Output(); err == nil {\n22\t\t\t// Trim trailing newline.\n23\t\t\ts := string(out)\n24\t\t\tif len(s) > 0 && s[len(s)-1] == '\\n' {\n25\t\t\t\ts = s[:len(s)-1]\n26\t\t\t}\n27\t\t\treturn s\n28\t\t}\n29\t\n30\t\tcwd, err := os.Getwd()\n31\t\tif err != nil {\n32\t\t\treturn \".\"\n33\t\t}\n34\t\n35\t\tdir := cwd\n36\t\tfor {\n37\t\t\tfor _, marker := range []string{\".git\", \".capy.toml\", \".capy\"} {\n38\t\t\t\tif _, err := os.Stat(filepath.Join(dir, marker)); err == nil {\n39\t\t\t\t\treturn dir\n40\t\t\t\t}\n41\t\t\t}\n42\t\t\tparent := filepath.Dir(dir)\n43\t\t\tif parent == dir {\n44\t\t\t\tbreak\n45\t\t\t}\n46\t\t\tdir = parent\n47\t\t}\n48\t\n49\t\treturn cwd\n50\t}\n51\t\n52\t// ProjectHash returns a deterministic 16-hex-char hash of the absolute project path.\n53\tfunc ProjectHash(dir string) string {\n54\t\tabs, _ := filepath.Abs(dir)\n55\t\th := sha256.Sum256([]byte(abs))\n56\t\treturn hex.EncodeToString(h[:8])\n57\t}\n58\t\n59\t// ResolveDBPath returns the path to the SQLite knowledge base.\n60\t// If Config.Store.Path is set, it is resolved relative to projectDir.\n61\t// Otherwise, the default XDG data location is used.\n62\tfunc (c *Config) ResolveDBPath(projectDir string) string {\n63\t\tif c.Store.Path != \"\" {\n64\t\t\tif filepath.IsAbs(c.Store.Path) {\n65\t\t\t\treturn c.Store.Path\n66\t\t\t}\n67\t\t\treturn filepath.Join(projectDir, c.Store.Path)\n68\t\t}\n69\t\n70\t\tdataHome := os.Getenv(\"XDG_DATA_HOME\")\n71\t\tif dataHome == \"\" {\n72\t\t\thome, _ := os.UserHomeDir()\n73\t\t\tdataHome = filepath.Join(home, \".local\", \"share\")\n74\t\t}\n75\t\thash := ProjectHash(projectDir)\n76\t\treturn filepath.Join(dataHome, \"capy\", hash, \"knowledge.db\")\n77\t}\n78\t"}]},"uuid":"13b2f2ff-5555-43b5-b798-d188f33a49a2","timestamp":"2026-04-23T18:44:16.462Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/config/paths.go","content":"package config\n\nimport (\n\t\"crypto/sha256\"\n\t\"encoding/hex\"\n\t\"os\"\n\t\"os/exec\"\n\t\"path/filepath\"\n)\n\n// DetectProjectRoot finds the project root directory using:\n//  1. CLAUDE_PROJECT_DIR env var\n//  2. git rev-parse --show-toplevel\n//  3. Walk up from cwd looking for .git/, .capy.toml, .capy/\n//  4. Fallback: cwd\nfunc DetectProjectRoot() string {\n\tif dir := os.Getenv(\"CLAUDE_PROJECT_DIR\"); dir != \"\" {\n\t\treturn dir\n\t}\n\n\tif out, err := exec.Command(\"git\", \"rev-parse\", \"--show-toplevel\").Output(); err == nil {\n\t\t// Trim trailing newline.\n\t\ts := string(out)\n\t\tif len(s) > 0 && s[len(s)-1] == '\\n' {\n\t\t\ts = s[:len(s)-1]\n\t\t}\n\t\treturn s\n\t}\n\n\tcwd, err := os.Getwd()\n\tif err != nil {\n\t\treturn \".\"\n\t}\n\n\tdir := cwd\n\tfor {\n\t\tfor _, marker := range []string{\".git\", \".capy.toml\", \".capy\"} {\n\t\t\tif _, err := os.Stat(filepath.Join(dir, marker)); err == nil {\n\t\t\t\treturn dir\n\t\t\t}\n\t\t}\n\t\tparent := filepath.Dir(dir)\n\t\tif parent == dir {\n\t\t\tbreak\n\t\t}\n\t\tdir = parent\n\t}\n\n\treturn cwd\n}\n\n// ProjectHash returns a deterministic 16-hex-char hash of the absolute project path.\nfunc ProjectHash(dir string) string {\n\tabs, _ := filepath.Abs(dir)\n\th := sha256.Sum256([]byte(abs))\n\treturn hex.EncodeToString(h[:8])\n}\n\n// ResolveDBPath returns the path to the SQLite knowledge base.\n// If Config.Store.Path is set, it is resolved relative to projectDir.\n// Otherwise, the default XDG data location is used.\nfunc (c *Config) ResolveDBPath(projectDir string) string {\n\tif c.Store.Path != \"\" {\n\t\tif filepath.IsAbs(c.Store.Path) {\n\t\t\treturn c.Store.Path\n\t\t}\n\t\treturn filepath.Join(projectDir, c.Store.Path)\n\t}\n\n\tdataHome := os.Getenv(\"XDG_DATA_HOME\")\n\tif dataHome == \"\" {\n\t\thome, _ := os.UserHomeDir()\n\t\tdataHome = filepath.Join(home, \".local\", \"share\")\n\t}\n\thash := ProjectHash(projectDir)\n\treturn filepath.Join(dataHome, \"capy\", hash, \"knowledge.db\")\n}\n","numLines":78,"startLine":1,"totalLines":78}},"sourceToolAssistantUUID":"1b2d5d75-c4f0-4903-a196-7af3a0c4e758","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"13b2f2ff-5555-43b5-b798-d188f33a49a2","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01SaXoXGyn8z1r3yfkJiPAvn","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"Ev8BClkIDRgCKkAZCwtQsRuHRGTPqlMclBEOscK35Kd9OC8z0sRJjh6OVks1/lly+cMmOoseceUI1MEKx9LDGJpErDqFfzhndcDNMg9jbGF1ZGUtb3B1cy00LTY4ABIMUZHgfuBUgvdE0YnXGgwbTtt07njbeFkZS+QiMJzhEgQyBHQdAdWmJQJ8KkVIfwJ1wIa5ZyAadlfjFS3JR6A4i4NviW0VkU8KqsI2XypUkhyDWezOqxMP1NKpgPukl8orSgab4KibYm6LozoT2UktiZ+iEQTNw6YKuZMoexdMKmmYVNe+zwQoSXjt/oK14nmD+ZeudrgZPkPu6J6uW+4sMaA6GAE="}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14771,"cache_read_input_tokens":50982,"output_tokens":296,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":14771,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCPDX4SGjcb3ra14bWE","type":"assistant","uuid":"51b30de8-fc70-44e0-96f1-bccac18425c4","timestamp":"2026-04-23T18:44:19.108Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"51b30de8-fc70-44e0-96f1-bccac18425c4","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01SaXoXGyn8z1r3yfkJiPAvn","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me check docs and the session end hook for additional context."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14771,"cache_read_input_tokens":50982,"output_tokens":296,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":14771,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCPDX4SGjcb3ra14bWE","type":"assistant","uuid":"4261a1ed-37fc-48fb-9580-4897ed545f6a","timestamp":"2026-04-23T18:44:20.036Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"4261a1ed-37fc-48fb-9580-4897ed545f6a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01SaXoXGyn8z1r3yfkJiPAvn","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_015JfdwnQ493nbUVW1NHohGj","name":"Read","input":{"file_path":"/home/sergio/Projects/personal/capy/internal/hook/sessionend.go"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14771,"cache_read_input_tokens":50982,"output_tokens":296,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":14771,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCPDX4SGjcb3ra14bWE","type":"assistant","uuid":"b6943b59-1b01-446f-bb0e-afa0dc7ef730","timestamp":"2026-04-23T18:44:20.614Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"b6943b59-1b01-446f-bb0e-afa0dc7ef730","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01SaXoXGyn8z1r3yfkJiPAvn","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QgyiJ2v2qwArDCRsaiDtNU","name":"Read","input":{"file_path":"/home/sergio/Projects/personal/capy/internal/config/config.go"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14771,"cache_read_input_tokens":50982,"output_tokens":296,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":14771,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCPDX4SGjcb3ra14bWE","type":"assistant","uuid":"73977849-ec25-4ff7-a35b-c828fc8eefdb","timestamp":"2026-04-23T18:44:21.116Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"73977849-ec25-4ff7-a35b-c828fc8eefdb","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01SaXoXGyn8z1r3yfkJiPAvn","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_0161SNKzvHfMFJpHyFuF4adw","name":"Bash","input":{"command":"ls /home/sergio/Projects/personal/capy/docs/ 2>/dev/null && echo \"---\" && ls /home/sergio/Projects/personal/capy/docs/wip/ 2>/dev/null; ls /home/sergio/Projects/personal/capy/CONTRIBUTING.md 2>/dev/null","description":"Check docs directory structure"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14771,"cache_read_input_tokens":50982,"output_tokens":296,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":14771,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCPDX4SGjcb3ra14bWE","type":"assistant","uuid":"9328fc7e-570c-425d-961a-e07988374318","timestamp":"2026-04-23T18:44:22.111Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"73977849-ec25-4ff7-a35b-c828fc8eefdb","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QgyiJ2v2qwArDCRsaiDtNU","type":"tool_result","content":"1\tpackage config\n2\t\n3\t// Config is the top-level configuration for capy.\n4\ttype Config struct {\n5\t\tStore    StoreConfig    `toml:\"store\"`\n6\t\tExecutor ExecutorConfig `toml:\"executor\"`\n7\t\tServer   ServerConfig   `toml:\"server\"`\n8\t}\n9\t\n10\t// StoreConfig controls the FTS5 knowledge base.\n11\ttype StoreConfig struct {\n12\t\tPath        string        `toml:\"path\"`\n13\t\tTitleWeight float64       `toml:\"title_weight\"` // BM25 title weight (default 2.0)\n14\t\tCleanup     CleanupConfig `toml:\"cleanup\"`\n15\t\tCache       CacheConfig   `toml:\"cache\"`\n16\t}\n17\t\n18\t// CacheConfig controls fetch TTL caching.\n19\ttype CacheConfig struct {\n20\t\tFetchTTLHours int `toml:\"fetch_ttl_hours\"` // default: 24\n21\t}\n22\t\n23\t// CleanupConfig controls cold-source pruning.\n24\t//\n25\t// EphemeralTTLHours sets the lifetime for ephemeral sources (command output,\n26\t// intent-search writes, batch buffers). Values < 1 are rejected at load time;\n27\t// 0 is not treated as \"disabled\" (there is no disabled mode) nor as \"purge\n28\t// everything\" (use `capy_cleanup purge_ephemeral=true` instead). Default 24.\n29\t// Longer values preserve more intra-session recall; shorter values reduce DB\n30\t// churn.\n31\ttype CleanupConfig struct {\n32\t\tColdThresholdDays int  `toml:\"cold_threshold_days\"`\n33\t\tEphemeralTTLHours int  `toml:\"ephemeral_ttl_hours\"`\n34\t\tAutoPrune         bool `toml:\"auto_prune\"`\n35\t}\n36\t\n37\t// ExecutorConfig controls the polyglot executor.\n38\ttype ExecutorConfig struct {\n39\t\tTimeout        int `toml:\"timeout\"`          // seconds\n40\t\tMaxOutputBytes int `toml:\"max_output_bytes\"` // hard cap on captured output\n41\t}\n42\t\n43\t// ServerConfig controls the MCP server.\n44\ttype ServerConfig struct {\n45\t\tLogLevel string `toml:\"log_level\"`\n46\t}\n47\t\n48\t// DefaultConfig returns a Config with sensible defaults.\n49\tfunc DefaultConfig() *Config {\n50\t\treturn &Config{\n51\t\t\tStore: StoreConfig{\n52\t\t\t\tTitleWeight: 2.0,\n53\t\t\t\tCleanup: CleanupConfig{\n54\t\t\t\t\tColdThresholdDays: 30,\n55\t\t\t\t\tEphemeralTTLHours: 24,\n56\t\t\t\t\tAutoPrune:         false,\n57\t\t\t\t},\n58\t\t\t\tCache: CacheConfig{\n59\t\t\t\t\tFetchTTLHours: 24,\n60\t\t\t\t},\n61\t\t\t},\n62\t\t\tExecutor: ExecutorConfig{\n63\t\t\t\tTimeout:        30,\n64\t\t\t\tMaxOutputBytes: 102400,\n65\t\t\t},\n66\t\t\tServer: ServerConfig{\n67\t\t\t\tLogLevel: \"info\",\n68\t\t\t},\n69\t\t}\n70\t}\n71\t"}]},"uuid":"f2dc08b1-fd74-477b-814c-7f39bfa905ab","timestamp":"2026-04-23T18:44:22.152Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/config/config.go","content":"package config\n\n// Config is the top-level configuration for capy.\ntype Config struct {\n\tStore    StoreConfig    `toml:\"store\"`\n\tExecutor ExecutorConfig `toml:\"executor\"`\n\tServer   ServerConfig   `toml:\"server\"`\n}\n\n// StoreConfig controls the FTS5 knowledge base.\ntype StoreConfig struct {\n\tPath        string        `toml:\"path\"`\n\tTitleWeight float64       `toml:\"title_weight\"` // BM25 title weight (default 2.0)\n\tCleanup     CleanupConfig `toml:\"cleanup\"`\n\tCache       CacheConfig   `toml:\"cache\"`\n}\n\n// CacheConfig controls fetch TTL caching.\ntype CacheConfig struct {\n\tFetchTTLHours int `toml:\"fetch_ttl_hours\"` // default: 24\n}\n\n// CleanupConfig controls cold-source pruning.\n//\n// EphemeralTTLHours sets the lifetime for ephemeral sources (command output,\n// intent-search writes, batch buffers). Values < 1 are rejected at load time;\n// 0 is not treated as \"disabled\" (there is no disabled mode) nor as \"purge\n// everything\" (use `capy_cleanup purge_ephemeral=true` instead). Default 24.\n// Longer values preserve more intra-session recall; shorter values reduce DB\n// churn.\ntype CleanupConfig struct {\n\tColdThresholdDays int  `toml:\"cold_threshold_days\"`\n\tEphemeralTTLHours int  `toml:\"ephemeral_ttl_hours\"`\n\tAutoPrune         bool `toml:\"auto_prune\"`\n}\n\n// ExecutorConfig controls the polyglot executor.\ntype ExecutorConfig struct {\n\tTimeout        int `toml:\"timeout\"`          // seconds\n\tMaxOutputBytes int `toml:\"max_output_bytes\"` // hard cap on captured output\n}\n\n// ServerConfig controls the MCP server.\ntype ServerConfig struct {\n\tLogLevel string `toml:\"log_level\"`\n}\n\n// DefaultConfig returns a Config with sensible defaults.\nfunc DefaultConfig() *Config {\n\treturn &Config{\n\t\tStore: StoreConfig{\n\t\t\tTitleWeight: 2.0,\n\t\t\tCleanup: CleanupConfig{\n\t\t\t\tColdThresholdDays: 30,\n\t\t\t\tEphemeralTTLHours: 24,\n\t\t\t\tAutoPrune:         false,\n\t\t\t},\n\t\t\tCache: CacheConfig{\n\t\t\t\tFetchTTLHours: 24,\n\t\t\t},\n\t\t},\n\t\tExecutor: ExecutorConfig{\n\t\t\tTimeout:        30,\n\t\t\tMaxOutputBytes: 102400,\n\t\t},\n\t\tServer: ServerConfig{\n\t\t\tLogLevel: \"info\",\n\t\t},\n\t}\n}\n","numLines":71,"startLine":1,"totalLines":71}},"sourceToolAssistantUUID":"73977849-ec25-4ff7-a35b-c828fc8eefdb","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"b6943b59-1b01-446f-bb0e-afa0dc7ef730","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015JfdwnQ493nbUVW1NHohGj","type":"tool_result","content":"1\tpackage hook\n2\t\n3\t// handleSessionEnd runs when a Claude Code session ends.\n4\t//\n5\t// WAL checkpointing is NOT done here — the MCP server's own Close() handles\n6\t// that when the process exits (via lifecycle guard). Opening a second DB\n7\t// connection from the hook while the server is still running prevents SQLite\n8\t// from getting exclusive WAL access, resulting in incomplete checkpoints.\n9\t//\n10\t// This handler is a no-op placeholder for future session-end cleanup tasks\n11\t// (e.g., session event logging, stats persistence).\n12\tfunc handleSessionEnd(projectDir string) {\n13\t\t// No-op. See ADR-016 for checkpoint strategy.\n14\t}\n15\t"}]},"uuid":"5b8b61ef-b24f-4d1e-ba2d-950f8eb662ef","timestamp":"2026-04-23T18:44:22.153Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/hook/sessionend.go","content":"package hook\n\n// handleSessionEnd runs when a Claude Code session ends.\n//\n// WAL checkpointing is NOT done here — the MCP server's own Close() handles\n// that when the process exits (via lifecycle guard). Opening a second DB\n// connection from the hook while the server is still running prevents SQLite\n// from getting exclusive WAL access, resulting in incomplete checkpoints.\n//\n// This handler is a no-op placeholder for future session-end cleanup tasks\n// (e.g., session event logging, stats persistence).\nfunc handleSessionEnd(projectDir string) {\n\t// No-op. See ADR-016 for checkpoint strategy.\n}\n","numLines":15,"startLine":1,"totalLines":15}},"sourceToolAssistantUUID":"b6943b59-1b01-446f-bb0e-afa0dc7ef730","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"4e537717-2cd8-451e-97e3-193ec2eb5106","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013n3JPwg798PkwNvvZSj5Xd","type":"tool_result","content":"1\tpackage store\n2\t\n3\timport (\n4\t\t\"encoding/json\"\n5\t\t\"strings\"\n6\t)\n7\t\n8\t// DetectContentType returns \"json\", \"markdown\", or \"plaintext\".\n9\tfunc DetectContentType(content string) string {\n10\t\ttrimmed := strings.TrimSpace(content)\n11\t\tif json.Valid([]byte(trimmed)) && len(trimmed) > 0 &&\n12\t\t\t(trimmed[0] == '{' || trimmed[0] == '[') {\n13\t\t\treturn \"json\"\n14\t\t}\n15\t\tif looksLikeMarkdown(trimmed) {\n16\t\t\treturn \"markdown\"\n17\t\t}\n18\t\treturn \"plaintext\"\n19\t}\n20\t\n21\tfunc looksLikeMarkdown(content string) bool {\n22\t\tlines := strings.SplitN(content, \"\\n\", 50)\n23\t\tindicators := 0\n24\t\tfor _, line := range lines {\n25\t\t\ttrimmed := strings.TrimSpace(line)\n26\t\t\tif strings.HasPrefix(trimmed, \"#\") {\n27\t\t\t\tindicators++\n28\t\t\t}\n29\t\t\tif strings.HasPrefix(trimmed, \"```\") {\n30\t\t\t\tindicators++\n31\t\t\t}\n32\t\t\tif strings.Contains(trimmed, \"](\") {\n33\t\t\t\tindicators++\n34\t\t\t}\n35\t\t\tif indicators >= 2 {\n36\t\t\t\treturn true\n37\t\t\t}\n38\t\t}\n39\t\treturn false\n40\t}\n41\t"}]},"uuid":"2cde12b1-1ed6-4f52-a671-182ffe690978","timestamp":"2026-04-23T18:44:25.613Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/detect.go","content":"package store\n\nimport (\n\t\"encoding/json\"\n\t\"strings\"\n)\n\n// DetectContentType returns \"json\", \"markdown\", or \"plaintext\".\nfunc DetectContentType(content string) string {\n\ttrimmed := strings.TrimSpace(content)\n\tif json.Valid([]byte(trimmed)) && len(trimmed) > 0 &&\n\t\t(trimmed[0] == '{' || trimmed[0] == '[') {\n\t\treturn \"json\"\n\t}\n\tif looksLikeMarkdown(trimmed) {\n\t\treturn \"markdown\"\n\t}\n\treturn \"plaintext\"\n}\n\nfunc looksLikeMarkdown(content string) bool {\n\tlines := strings.SplitN(content, \"\\n\", 50)\n\tindicators := 0\n\tfor _, line := range lines {\n\t\ttrimmed := strings.TrimSpace(line)\n\t\tif strings.HasPrefix(trimmed, \"#\") {\n\t\t\tindicators++\n\t\t}\n\t\tif strings.HasPrefix(trimmed, \"```\") {\n\t\t\tindicators++\n\t\t}\n\t\tif strings.Contains(trimmed, \"](\") {\n\t\t\tindicators++\n\t\t}\n\t\tif indicators >= 2 {\n\t\t\treturn true\n\t\t}\n\t}\n\treturn false\n}\n","numLines":41,"startLine":1,"totalLines":41}},"sourceToolAssistantUUID":"4e537717-2cd8-451e-97e3-193ec2eb5106","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"14119f30-408e-4694-a9ce-00ac93d0c8a7","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017uRJijKC9eBgzNiqdETwvd","type":"tool_result","content":"1\t# Contributing to capy\n2\t\n3\t## Local Setup\n4\t\n5\t### Prerequisites\n6\t\n7\t- **Go 1.23+** ([install](https://go.dev/dl/))\n8\t- **C compiler** — required for CGO (SQLite FTS5):\n9\t  - macOS: `xcode-select --install`\n10\t  - Debian/Ubuntu: `sudo apt install build-essential`\n11\t  - Fedora: `sudo dnf install gcc`\n12\t- **Language runtimes** (optional) — for testing the executor against specific languages:\n13\t  - At minimum: `bash`, `python3`\n14\t  - Full set: `node`/`bun`, `tsx`/`ts-node`, `ruby`, `go`, `rustc`, `php`, `perl`, `Rscript`, `elixir`\n15\t\n16\t### Clone and Build\n17\t\n18\t```bash\n19\tgit clone https://github.com/serpro69/capy.git\n20\tcd capy\n21\tmake build\n22\t```\n23\t\n24\tThis produces a `./capy` binary. The `-tags fts5` build tag is handled by the Makefile.\n25\t\n26\t### Verify\n27\t\n28\t```bash\n29\tmake test       # run all tests\n30\tmake vet        # static analysis\n31\tmake test-race  # tests with race detector\n32\t```\n33\t\n34\t## Project Structure\n35\t\n36\t```\n37\tcmd/capy/           CLI entry points (serve, hook, setup, doctor, cleanup)\n38\tinternal/\n39\t  adapter/          Platform adapter interface + Claude Code implementation\n40\t  config/           TOML config loading, project root detection, path resolution\n41\t  executor/         Polyglot code executor (11 languages, process isolation)\n42\t  hook/             Hook event routing (PreToolUse, PostToolUse, etc.)\n43\t  platform/         Setup command, doctor diagnostics, routing instructions\n44\t  security/         Settings parsing, glob matching, command splitting, shell-escape detection\n45\t  server/           MCP server, 9 tool handlers, stats, lifecycle, snippets\n46\t  store/            SQLite FTS5 knowledge base (schema, indexing, chunking, search, cleanup)\n47\t  version/          Version variable (set at build via ldflags)\n48\t```\n49\t\n50\t## Testing\n51\t\n52\t### Running Tests\n53\t\n54\tAll tests require the `fts5` build tag. The Makefile handles this:\n55\t\n56\t```bash\n57\tmake test                                         # all tests\n58\tmake test-race                                    # with race detector\n59\tgo test -tags fts5 -count=1 ./internal/store/...  # single package\n60\tgo test -tags fts5 -count=1 -run TestSearch ./internal/store/...  # single test\n61\tgo test -tags fts5 -count=1 -v ./internal/hook/...  # verbose\n62\t```\n63\t\n64\tWithout `-tags fts5` you'll get cryptic `no such module: fts5` errors from SQLite. This is the #1 gotcha.\n65\t\n66\t### Coverage\n67\t\n68\t```bash\n69\tCGO_ENABLED=1 go test -tags fts5 -coverprofile=cover.out ./...\n70\tgo tool cover -func=cover.out | tail -1           # total percentage\n71\tgo tool cover -html=cover.out -o cover.html       # visual report\n72\t```\n73\t\n74\t### Test Organization\n75\t\n76\tEach package has two levels of tests:\n77\t\n78\t- **Unit tests** (`*_test.go`) — test individual functions in isolation. Use test stubs/mocks. Fast.\n79\t- **Integration tests** (`integration_test.go`) — test the full pipeline across packages. Use real adapters, real SQLite, real executor. Found in `internal/server/` and `internal/hook/`.\n80\t\n81\tKey integration test files:\n82\t\n83\t| File | What it covers |\n84\t|------|----------------|\n85\t| `server/integration_test.go` | MCP tool handler -> executor -> store -> search round-trips |\n86\t| `hook/integration_test.go` | Full hook JSON through Claude Code adapter with real routing |\n87\t\n88\t## Local Verification Without Installation\n89\t\n90\tYou don't need to install capy globally to test it. Build and run from the repo root.\n91\t\n92\t### Testing Hooks Manually\n93\t\n94\tBuild the binary and pipe JSON to stdin:\n95\t\n96\t```bash\n97\tmake build\n98\t\n99\t# Test: curl gets intercepted\n100\techo '{\"tool_name\":\"Bash\",\"tool_input\":{\"command\":\"curl https://example.com\"},\"session_id\":\"test\"}' \\\n101\t  | ./capy hook pretooluse | python3 -m json.tool\n102\t\n103\t# Expected: permissionDecision \"allow\" with updatedInput replacing curl with echo message\n104\t\n105\t# Test: WebFetch gets denied\n106\techo '{\"tool_name\":\"WebFetch\",\"tool_input\":{\"url\":\"https://example.com\"},\"session_id\":\"test\"}' \\\n107\t  | ./capy hook pretooluse | python3 -m json.tool\n108\t\n109\t# Expected: permissionDecision \"deny\"\n110\t\n111\t# Test: normal bash gets guidance\n112\techo '{\"tool_name\":\"Bash\",\"tool_input\":{\"command\":\"ls -la\"},\"session_id\":\"test\"}' \\\n113\t  | ./capy hook pretooluse | python3 -m json.tool\n114\t\n115\t# Expected: additionalContext with capy guidance (or empty if guidance was already shown this session)\n116\t\n117\t# Test: security deny\n118\techo '{\"tool_name\":\"Bash\",\"tool_input\":{\"command\":\"sudo rm -rf /\"},\"session_id\":\"test\"}' \\\n119\t  | ./capy hook pretooluse --project-dir . | python3 -m json.tool\n120\t\n121\t# Expected: permissionDecision \"deny\" (if you have a Bash(sudo *) deny rule in .claude/settings.json)\n122\t```\n123\t\n124\t### Testing Doctor\n125\t\n126\t```bash\n127\t./capy doctor\n128\t./capy doctor --project-dir /path/to/some/project\n129\t```\n130\t\n131\tThis shows diagnostics without modifying anything. Useful to verify runtimes, FTS5, and config loading.\n132\t\n133\t### Testing With Claude Code (Full E2E)\n134\t\n135\tFor a full end-to-end test, point `capy setup` at a scratch project using the local binary:\n136\t\n137\t```bash\n138\t# Create a scratch project\n139\tmkdir /tmp/capy-test && cd /tmp/capy-test\n140\tgit init\n141\t\n142\t# Setup using your local binary\n143\t/path/to/capy/capy setup --binary /path/to/capy/capy\n144\t\n145\t# Verify\n146\t/path/to/capy/capy doctor\n147\t\n148\t# Now open this project in Claude Code — hooks and MCP tools should be active\n149\t```\n150\t\n151\tTo iterate: rebuild with `make build`, then restart Claude Code (the MCP server and hooks pick up the new binary automatically since the config points to the absolute path).\n152\t\n153\t### Testing the MCP Server Directly\n154\t\n155\tThe MCP server uses stdio (JSON-RPC over stdin/stdout). You can test it by sending raw JSON-RPC messages, but this is complex. The integration tests in `internal/server/integration_test.go` cover this path — prefer running those:\n156\t\n157\t```bash\n158\tgo test -tags fts5 -count=1 -v -run TestIntegration ./internal/server/...\n159\t```\n160\t\n161\t## Development Workflow\n162\t\n163\t### Making Changes\n164\t\n165\t1. Find the relevant package in `internal/`\n166\t2. Read existing tests to understand the patterns\n167\t3. Write or modify code\n168\t4. Run the package tests: `go test -tags fts5 -count=1 ./internal/<package>/...`\n169\t5. Run `make vet` for static analysis\n170\t6. Run `make test` for the full suite\n171\t7. If you changed hook behavior, test manually with piped JSON (see above)\n172\t\n173\t### Common Patterns\n174\t\n175\t**Tool handlers** (`server/tool_*.go`): Each MCP tool has a handler function that:\n176\t1. Parses arguments from the request (with input coercion for double-serialized JSON)\n177\t2. Runs security checks\n178\t3. Does the work (execute, index, search, etc.)\n179\t4. Tracks stats via `s.trackToolResponse()`\n180\t5. Returns `*mcp.CallToolResult`\n181\t\n182\t**Store operations**: All database operations use prepared statements cached on the `ContentStore` struct. New queries need a prepared statement added to `store.go:prepareStatements()` and closed in `store.go:Close()`.\n183\t\n184\t**SQLite WAL checkpoint** (see ADR-015, ADR-016): The knowledge DB uses WAL mode. On `Close()`, the WAL must be flushed into the main `.db` file — otherwise git operations corrupt the database (WAL/SHM sidecar files aren't tracked). The checkpoint requires exclusive WAL access, which means the `database/sql` connection pool must be closed *before* checkpointing. `Close()` handles this by: (1) closing statements, (2) closing the pool, (3) opening a fresh single connection for `PRAGMA wal_checkpoint(TRUNCATE)`. Do not attempt to checkpoint while pool connections are open — it silently degrades to passive (incomplete). The `Checkpoint()` method does the same thing standalone for the `capy checkpoint` CLI command.\n185\t\n186\t**Important nuance**: WAL/SHM files only exist when the DB has been written to during a session. `Close()` checkpoints whatever WAL frames the current session created. If the server starts but no writes happen (e.g., empty `capy serve` → Ctrl+C), there's nothing to checkpoint and any pre-existing WAL files from a *previous* session remain untouched. This means stale WAL files from an older binary version or unclean shutdown require a manual `capy checkpoint` to flush.\n187\t\n188\t**Security checks**: Bash deny patterns are loaded once at server startup. The `matchesAnyBashPattern` function uses cached regexes (`sync.Map`). Shell-escape patterns for non-shell languages are compiled once in `init()`.\n189\t\n190\t**Hook routing** (`hook/pretooluse.go`): The main routing function dispatches on canonical tool name. New tool interceptions go here. Guidance uses file-based persistence (`.capy/guidance-<sessionID>.json`) since hooks run as separate short-lived processes.\n191\t\n192\t### Adding a New MCP Tool\n193\t\n194\t1. Define the tool schema in `server/tools.go` (follow existing patterns)\n195\t2. Create the handler in a new `server/tool_<name>.go` file\n196\t3. Register it in `server/tools.go:registerTools()`\n197\t4. Add the tool name to `platform/routing.go:CapyToolNames`\n198\t5. Write unit tests in `server/tool_<name>_test.go`\n199\t6. Add an integration test in `server/integration_test.go` if the tool interacts with the store\n200\t\n201\t### Adding a New Hook Interception\n202\t\n203\t1. Add the routing logic to `hook/pretooluse.go:handlePreToolUse()`\n204\t2. If it's a new canonical tool, add it to `hook/helpers.go:toolAliases` for platform variants\n205\t3. Add the tool name to `platform/setup.go:PreToolUseMatcherPattern` so the hook is registered\n206\t4. Write tests in `hook/hook_test.go` (unit, with test adapter) and `hook/integration_test.go` (with Claude Code adapter)\n207\t\n208\t## Releases\n209\t\n210\tReleases are fully automated. Push a semver tag to trigger the pipeline:\n211\t\n212\t```bash\n213\tgit tag v1.0.0 && git push origin v1.0.0\n214\t```\n215\t\n216\tWhat happens:\n217\t1. **CI** runs vet + tests (same as every push to master)\n218\t2. **Build** produces binaries on native runners for 3 platforms (darwin/arm64, linux/amd64, linux/arm64)\n219\t3. **Release** creates a GitHub Release with tarballs and SHA256SUMS\n220\t4. **Homebrew** updates the `serpro69/homebrew-tap` formula (stable releases only)\n221\t\n222\tPre-release tags (e.g., `v1.0.0-rc.1`) create pre-release GitHub Releases and skip the Homebrew update.\n223\t\n224\t## Code Conventions\n225\t\n226\t- **Error handling**: Wrap errors with context via `fmt.Errorf(\"doing X: %w\", err)`. Don't swallow errors silently — at minimum log with `slog.Debug` or `slog.Warn`.\n227\t- **Concurrency**: Use `sync.Mutex` for mutable state, `sync.Once` for lazy init, `sync.Map` for concurrent caches. No naked goroutines that use shared resources without synchronization.\n228\t- **No `init()` side effects**: The only `init()` in the codebase compiles regex patterns (`security/shell_escape.go`). Keep it that way.\n229\t- **Tests**: Use `testify/assert` and `testify/require`. `require` for preconditions (test stops on failure), `assert` for the actual check.\n230\t- **Build tags**: Always pass `-tags fts5` for anything involving the store or server packages.\n231\t"}]},"uuid":"06f255e1-3d8a-4b6a-a62c-b2d67065a17c","timestamp":"2026-04-23T18:44:25.629Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/CONTRIBUTING.md","content":"# Contributing to capy\n\n## Local Setup\n\n### Prerequisites\n\n- **Go 1.23+** ([install](https://go.dev/dl/))\n- **C compiler** — required for CGO (SQLite FTS5):\n  - macOS: `xcode-select --install`\n  - Debian/Ubuntu: `sudo apt install build-essential`\n  - Fedora: `sudo dnf install gcc`\n- **Language runtimes** (optional) — for testing the executor against specific languages:\n  - At minimum: `bash`, `python3`\n  - Full set: `node`/`bun`, `tsx`/`ts-node`, `ruby`, `go`, `rustc`, `php`, `perl`, `Rscript`, `elixir`\n\n### Clone and Build\n\n```bash\ngit clone https://github.com/serpro69/capy.git\ncd capy\nmake build\n```\n\nThis produces a `./capy` binary. The `-tags fts5` build tag is handled by the Makefile.\n\n### Verify\n\n```bash\nmake test       # run all tests\nmake vet        # static analysis\nmake test-race  # tests with race detector\n```\n\n## Project Structure\n\n```\ncmd/capy/           CLI entry points (serve, hook, setup, doctor, cleanup)\ninternal/\n  adapter/          Platform adapter interface + Claude Code implementation\n  config/           TOML config loading, project root detection, path resolution\n  executor/         Polyglot code executor (11 languages, process isolation)\n  hook/             Hook event routing (PreToolUse, PostToolUse, etc.)\n  platform/         Setup command, doctor diagnostics, routing instructions\n  security/         Settings parsing, glob matching, command splitting, shell-escape detection\n  server/           MCP server, 9 tool handlers, stats, lifecycle, snippets\n  store/            SQLite FTS5 knowledge base (schema, indexing, chunking, search, cleanup)\n  version/          Version variable (set at build via ldflags)\n```\n\n## Testing\n\n### Running Tests\n\nAll tests require the `fts5` build tag. The Makefile handles this:\n\n```bash\nmake test                                         # all tests\nmake test-race                                    # with race detector\ngo test -tags fts5 -count=1 ./internal/store/...  # single package\ngo test -tags fts5 -count=1 -run TestSearch ./internal/store/...  # single test\ngo test -tags fts5 -count=1 -v ./internal/hook/...  # verbose\n```\n\nWithout `-tags fts5` you'll get cryptic `no such module: fts5` errors from SQLite. This is the #1 gotcha.\n\n### Coverage\n\n```bash\nCGO_ENABLED=1 go test -tags fts5 -coverprofile=cover.out ./...\ngo tool cover -func=cover.out | tail -1           # total percentage\ngo tool cover -html=cover.out -o cover.html       # visual report\n```\n\n### Test Organization\n\nEach package has two levels of tests:\n\n- **Unit tests** (`*_test.go`) — test individual functions in isolation. Use test stubs/mocks. Fast.\n- **Integration tests** (`integration_test.go`) — test the full pipeline across packages. Use real adapters, real SQLite, real executor. Found in `internal/server/` and `internal/hook/`.\n\nKey integration test files:\n\n| File | What it covers |\n|------|----------------|\n| `server/integration_test.go` | MCP tool handler -> executor -> store -> search round-trips |\n| `hook/integration_test.go` | Full hook JSON through Claude Code adapter with real routing |\n\n## Local Verification Without Installation\n\nYou don't need to install capy globally to test it. Build and run from the repo root.\n\n### Testing Hooks Manually\n\nBuild the binary and pipe JSON to stdin:\n\n```bash\nmake build\n\n# Test: curl gets intercepted\necho '{\"tool_name\":\"Bash\",\"tool_input\":{\"command\":\"curl https://example.com\"},\"session_id\":\"test\"}' \\\n  | ./capy hook pretooluse | python3 -m json.tool\n\n# Expected: permissionDecision \"allow\" with updatedInput replacing curl with echo message\n\n# Test: WebFetch gets denied\necho '{\"tool_name\":\"WebFetch\",\"tool_input\":{\"url\":\"https://example.com\"},\"session_id\":\"test\"}' \\\n  | ./capy hook pretooluse | python3 -m json.tool\n\n# Expected: permissionDecision \"deny\"\n\n# Test: normal bash gets guidance\necho '{\"tool_name\":\"Bash\",\"tool_input\":{\"command\":\"ls -la\"},\"session_id\":\"test\"}' \\\n  | ./capy hook pretooluse | python3 -m json.tool\n\n# Expected: additionalContext with capy guidance (or empty if guidance was already shown this session)\n\n# Test: security deny\necho '{\"tool_name\":\"Bash\",\"tool_input\":{\"command\":\"sudo rm -rf /\"},\"session_id\":\"test\"}' \\\n  | ./capy hook pretooluse --project-dir . | python3 -m json.tool\n\n# Expected: permissionDecision \"deny\" (if you have a Bash(sudo *) deny rule in .claude/settings.json)\n```\n\n### Testing Doctor\n\n```bash\n./capy doctor\n./capy doctor --project-dir /path/to/some/project\n```\n\nThis shows diagnostics without modifying anything. Useful to verify runtimes, FTS5, and config loading.\n\n### Testing With Claude Code (Full E2E)\n\nFor a full end-to-end test, point `capy setup` at a scratch project using the local binary:\n\n```bash\n# Create a scratch project\nmkdir /tmp/capy-test && cd /tmp/capy-test\ngit init\n\n# Setup using your local binary\n/path/to/capy/capy setup --binary /path/to/capy/capy\n\n# Verify\n/path/to/capy/capy doctor\n\n# Now open this project in Claude Code — hooks and MCP tools should be active\n```\n\nTo iterate: rebuild with `make build`, then restart Claude Code (the MCP server and hooks pick up the new binary automatically since the config points to the absolute path).\n\n### Testing the MCP Server Directly\n\nThe MCP server uses stdio (JSON-RPC over stdin/stdout). You can test it by sending raw JSON-RPC messages, but this is complex. The integration tests in `internal/server/integration_test.go` cover this path — prefer running those:\n\n```bash\ngo test -tags fts5 -count=1 -v -run TestIntegration ./internal/server/...\n```\n\n## Development Workflow\n\n### Making Changes\n\n1. Find the relevant package in `internal/`\n2. Read existing tests to understand the patterns\n3. Write or modify code\n4. Run the package tests: `go test -tags fts5 -count=1 ./internal/<package>/...`\n5. Run `make vet` for static analysis\n6. Run `make test` for the full suite\n7. If you changed hook behavior, test manually with piped JSON (see above)\n\n### Common Patterns\n\n**Tool handlers** (`server/tool_*.go`): Each MCP tool has a handler function that:\n1. Parses arguments from the request (with input coercion for double-serialized JSON)\n2. Runs security checks\n3. Does the work (execute, index, search, etc.)\n4. Tracks stats via `s.trackToolResponse()`\n5. Returns `*mcp.CallToolResult`\n\n**Store operations**: All database operations use prepared statements cached on the `ContentStore` struct. New queries need a prepared statement added to `store.go:prepareStatements()` and closed in `store.go:Close()`.\n\n**SQLite WAL checkpoint** (see ADR-015, ADR-016): The knowledge DB uses WAL mode. On `Close()`, the WAL must be flushed into the main `.db` file — otherwise git operations corrupt the database (WAL/SHM sidecar files aren't tracked). The checkpoint requires exclusive WAL access, which means the `database/sql` connection pool must be closed *before* checkpointing. `Close()` handles this by: (1) closing statements, (2) closing the pool, (3) opening a fresh single connection for `PRAGMA wal_checkpoint(TRUNCATE)`. Do not attempt to checkpoint while pool connections are open — it silently degrades to passive (incomplete). The `Checkpoint()` method does the same thing standalone for the `capy checkpoint` CLI command.\n\n**Important nuance**: WAL/SHM files only exist when the DB has been written to during a session. `Close()` checkpoints whatever WAL frames the current session created. If the server starts but no writes happen (e.g., empty `capy serve` → Ctrl+C), there's nothing to checkpoint and any pre-existing WAL files from a *previous* session remain untouched. This means stale WAL files from an older binary version or unclean shutdown require a manual `capy checkpoint` to flush.\n\n**Security checks**: Bash deny patterns are loaded once at server startup. The `matchesAnyBashPattern` function uses cached regexes (`sync.Map`). Shell-escape patterns for non-shell languages are compiled once in `init()`.\n\n**Hook routing** (`hook/pretooluse.go`): The main routing function dispatches on canonical tool name. New tool interceptions go here. Guidance uses file-based persistence (`.capy/guidance-<sessionID>.json`) since hooks run as separate short-lived processes.\n\n### Adding a New MCP Tool\n\n1. Define the tool schema in `server/tools.go` (follow existing patterns)\n2. Create the handler in a new `server/tool_<name>.go` file\n3. Register it in `server/tools.go:registerTools()`\n4. Add the tool name to `platform/routing.go:CapyToolNames`\n5. Write unit tests in `server/tool_<name>_test.go`\n6. Add an integration test in `server/integration_test.go` if the tool interacts with the store\n\n### Adding a New Hook Interception\n\n1. Add the routing logic to `hook/pretooluse.go:handlePreToolUse()`\n2. If it's a new canonical tool, add it to `hook/helpers.go:toolAliases` for platform variants\n3. Add the tool name to `platform/setup.go:PreToolUseMatcherPattern` so the hook is registered\n4. Write tests in `hook/hook_test.go` (unit, with test adapter) and `hook/integration_test.go` (with Claude Code adapter)\n\n## Releases\n\nReleases are fully automated. Push a semver tag to trigger the pipeline:\n\n```bash\ngit tag v1.0.0 && git push origin v1.0.0\n```\n\nWhat happens:\n1. **CI** runs vet + tests (same as every push to master)\n2. **Build** produces binaries on native runners for 3 platforms (darwin/arm64, linux/amd64, linux/arm64)\n3. **Release** creates a GitHub Release with tarballs and SHA256SUMS\n4. **Homebrew** updates the `serpro69/homebrew-tap` formula (stable releases only)\n\nPre-release tags (e.g., `v1.0.0-rc.1`) create pre-release GitHub Releases and skip the Homebrew update.\n\n## Code Conventions\n\n- **Error handling**: Wrap errors with context via `fmt.Errorf(\"doing X: %w\", err)`. Don't swallow errors silently — at minimum log with `slog.Debug` or `slog.Warn`.\n- **Concurrency**: Use `sync.Mutex` for mutable state, `sync.Once` for lazy init, `sync.Map` for concurrent caches. No naked goroutines that use shared resources without synchronization.\n- **No `init()` side effects**: The only `init()` in the codebase compiles regex patterns (`security/shell_escape.go`). Keep it that way.\n- **Tests**: Use `testify/assert` and `testify/require`. `require` for preconditions (test stops on failure), `assert` for the actual check.\n- **Build tags**: Always pass `-tags fts5` for anything involving the store or server packages.\n","numLines":231,"startLine":1,"totalLines":231}},"sourceToolAssistantUUID":"14119f30-408e-4694-a9ce-00ac93d0c8a7","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"291b6f84-2ad2-4e13-bcd3-eeb9d94a357f","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015q8VBZZv2zmFK1qiqxi6TK","type":"tool_result","content":"1\tpackage store\n2\t\n3\timport (\n4\t\t\"context\"\n5\t\t\"database/sql\"\n6\t\t\"fmt\"\n7\t\t\"log/slog\"\n8\t\t\"os\"\n9\t\t\"path/filepath\"\n10\t\t\"sync\"\n11\t\t\"sync/atomic\"\n12\t\n13\t\t_ \"github.com/mattn/go-sqlite3\"\n14\t)\n15\t\n16\tconst fuzzyCacheMaxSize = 256\n17\t\n18\tconst optimizeEvery int64 = 50\n19\t\n20\tfunc (s *ContentStore) ctx() context.Context {\n21\t\treturn context.Background()\n22\t}\n23\t\n24\t// ContentStore manages the FTS5 knowledge base.\n25\ttype ContentStore struct {\n26\t\tdbPath      string\n27\t\tprojectDir  string\n28\t\ttitleWeight float64\n29\t\n30\t\tmu sync.Mutex\n31\t\tdb *sql.DB\n32\t\n33\t\t// Prepared statements — indexing.\n34\t\tstmtInsertSource          *sql.Stmt\n35\t\tstmtInsertChunk           *sql.Stmt\n36\t\tstmtInsertTrigram         *sql.Stmt\n37\t\tstmtInsertVocab           *sql.Stmt\n38\t\tstmtDeleteChunksBySource  *sql.Stmt\n39\t\tstmtDeleteTrigramBySource *sql.Stmt\n40\t\tstmtDeleteSource          *sql.Stmt\n41\t\tstmtFindSourceByLabel     *sql.Stmt\n42\t\tstmtUpdateSourceAccess    *sql.Stmt\n43\t\tstmtUpdateSourceKind      *sql.Stmt\n44\t\n45\t\tinsertCount atomic.Int64\n46\t\n47\t\t// Fuzzy correction cache: nil value = \"no correction\"; key-missing = \"not cached\".\n48\t\tfuzzyCacheMu sync.RWMutex\n49\t\tfuzzyCache   map[string]*string\n50\t\n51\t\t// Prepared statements — search.\n52\t\tstmtFuzzyVocab *sql.Stmt\n53\t\n54\t\t// Prepared statements — queries.\n55\t\tstmtGetSourceMeta    *sql.Stmt\n56\t\tstmtListSources      *sql.Stmt\n57\t\tstmtChunksBySource   *sql.Stmt\n58\t\tstmtSourceChunkCount *sql.Stmt\n59\t\tstmtChunkContent     *sql.Stmt\n60\t\tstmtTrackAccess      *sql.Stmt\n61\t}\n62\t\n63\t// NewContentStore creates a new ContentStore. The database is not opened\n64\t// until the first operation (lazy initialization via getDB).\n65\t// titleWeight controls the BM25 title column weight; values <= 0 default to 2.0.\n66\tfunc NewContentStore(dbPath, projectDir string, titleWeight float64) *ContentStore {\n67\t\tif titleWeight <= 0 {\n68\t\t\ttitleWeight = 2.0\n69\t\t}\n70\t\treturn &ContentStore{\n71\t\t\tdbPath:      dbPath,\n72\t\t\tprojectDir:  projectDir,\n73\t\t\ttitleWeight: titleWeight,\n74\t\t\tfuzzyCache:  make(map[string]*string),\n75\t\t}\n76\t}\n77\t\n78\t// getDB returns the database connection, initializing it on first call.\n79\t// On corruption, it backs up the corrupt file and retries once.\n80\tfunc (s *ContentStore) getDB() (*sql.DB, error) {\n81\t\ts.mu.Lock()\n82\t\tdefer s.mu.Unlock()\n83\t\n84\t\tif s.db != nil {\n85\t\t\treturn s.db, nil\n86\t\t}\n87\t\n88\t\tdbDir := filepath.Dir(s.dbPath)\n89\t\tif err := os.MkdirAll(dbDir, 0o755); err != nil {\n90\t\t\treturn nil, fmt.Errorf(\"creating DB directory: %w\", err)\n91\t\t}\n92\t\n93\t\tif s.projectDir != \"\" {\n94\t\t\t_ = os.WriteFile(filepath.Join(dbDir, \".project\"), []byte(s.projectDir+\"\\n\"), 0o644)\n95\t\t}\n96\t\n97\t\tdb, err := s.openDB()\n98\t\tif err != nil && isSQLiteCorruption(err) {\n99\t\t\tslog.Warn(\"corrupt database detected, backing up and recreating\", \"path\", s.dbPath, \"error\", err)\n100\t\t\tbackupCorruptDB(s.dbPath)\n101\t\t\tdb, err = s.openDB()\n102\t\t\tif err != nil {\n103\t\t\t\treturn nil, fmt.Errorf(\"opening database after recovery: %w\", err)\n104\t\t\t}\n105\t\t}\n106\t\tif err != nil {\n107\t\t\treturn nil, err\n108\t\t}\n109\t\n110\t\ts.db = db\n111\t\treturn db, nil\n112\t}\n113\t\n114\tfunc (s *ContentStore) openDB() (*sql.DB, error) {\n115\t\tdsn := s.dbPath + \"?_journal_mode=WAL&_synchronous=NORMAL&_busy_timeout=5000&_foreign_keys=ON\"\n116\t\tdb, err := sql.Open(\"sqlite3\", dsn)\n117\t\tif err != nil {\n118\t\t\treturn nil, fmt.Errorf(\"opening database: %w\", err)\n119\t\t}\n120\t\n121\t\tif _, err := db.Exec(\"PRAGMA mmap_size = 268435456\"); err != nil {\n122\t\t\tslog.Warn(\"failed to set mmap_size pragma\", \"error\", err)\n123\t\t}\n124\t\n125\t\tif _, err := db.Exec(schemaSQL); err != nil {\n126\t\t\tdb.Close()\n127\t\t\treturn nil, fmt.Errorf(\"initializing schema: %w\", err)\n128\t\t}\n129\t\n130\t\tif err := applyMigrations(db); err != nil {\n131\t\t\tdb.Close()\n132\t\t\treturn nil, fmt.Errorf(\"applying migrations: %w\", err)\n133\t\t}\n134\t\n135\t\tif err := s.prepareStatements(db); err != nil {\n136\t\t\tdb.Close()\n137\t\t\treturn nil, fmt.Errorf(\"preparing statements: %w\", err)\n138\t\t}\n139\t\n140\t\treturn db, nil\n141\t}\n142\t\n143\tfunc (s *ContentStore) prepareStatements(db *sql.DB) error {\n144\t\tvar err error\n145\t\n146\t\t// --- Indexing ---\n147\t\n148\t\ts.stmtInsertSource, err = db.Prepare(`\n149\t\t\tINSERT INTO sources (label, content_type, chunk_count, code_chunk_count, content_hash, kind)\n150\t\t\tVALUES (?, ?, ?, ?, ?, ?)`)\n151\t\tif err != nil {\n152\t\t\treturn err\n153\t\t}\n154\t\n155\t\ts.stmtInsertChunk, err = db.Prepare(`\n156\t\t\tINSERT INTO chunks (title, content, source_id, content_type)\n157\t\t\tVALUES (?, ?, ?, ?)`)\n158\t\tif err != nil {\n159\t\t\treturn err\n160\t\t}\n161\t\n162\t\ts.stmtInsertTrigram, err = db.Prepare(`\n163\t\t\tINSERT INTO chunks_trigram (title, content, source_id, content_type)\n164\t\t\tVALUES (?, ?, ?, ?)`)\n165\t\tif err != nil {\n166\t\t\treturn err\n167\t\t}\n168\t\n169\t\ts.stmtInsertVocab, err = db.Prepare(`INSERT OR IGNORE INTO vocabulary (word) VALUES (?)`)\n170\t\tif err != nil {\n171\t\t\treturn err\n172\t\t}\n173\t\n174\t\ts.stmtDeleteChunksBySource, err = db.Prepare(`DELETE FROM chunks WHERE source_id = ?`)\n175\t\tif err != nil {\n176\t\t\treturn err\n177\t\t}\n178\t\n179\t\ts.stmtDeleteTrigramBySource, err = db.Prepare(`DELETE FROM chunks_trigram WHERE source_id = ?`)\n180\t\tif err != nil {\n181\t\t\treturn err\n182\t\t}\n183\t\n184\t\ts.stmtDeleteSource, err = db.Prepare(`DELETE FROM sources WHERE id = ?`)\n185\t\tif err != nil {\n186\t\t\treturn err\n187\t\t}\n188\t\n189\t\ts.stmtFindSourceByLabel, err = db.Prepare(`\n190\t\t\tSELECT id, content_hash, kind FROM sources WHERE label = ?`)\n191\t\tif err != nil {\n192\t\t\treturn err\n193\t\t}\n194\t\n195\t\ts.stmtUpdateSourceAccess, err = db.Prepare(`\n196\t\t\tUPDATE sources SET last_accessed_at = datetime('now') WHERE label = ? AND content_hash = ?`)\n197\t\tif err != nil {\n198\t\t\treturn err\n199\t\t}\n200\t\n201\t\ts.stmtUpdateSourceKind, err = db.Prepare(`\n202\t\t\tUPDATE sources SET kind = ?, last_accessed_at = datetime('now') WHERE id = ?`)\n203\t\tif err != nil {\n204\t\t\treturn err\n205\t\t}\n206\t\n207\t\t// --- Search ---\n208\t\n209\t\ts.stmtFuzzyVocab, err = db.Prepare(`\n210\t\t\tSELECT word FROM vocabulary WHERE length(word) BETWEEN ? AND ?`)\n211\t\tif err != nil {\n212\t\t\treturn err\n213\t\t}\n214\t\n215\t\t// --- Queries ---\n216\t\n217\t\ts.stmtGetSourceMeta, err = db.Prepare(`\n218\t\t\tSELECT label, chunk_count, indexed_at, kind FROM sources WHERE label = ?`)\n219\t\tif err != nil {\n220\t\t\treturn err\n221\t\t}\n222\t\n223\t\ts.stmtListSources, err = db.Prepare(`\n224\t\t\tSELECT id, label, content_type, chunk_count, code_chunk_count,\n225\t\t\t\tindexed_at, last_accessed_at, access_count, content_hash, kind\n226\t\t\tFROM sources ORDER BY id DESC`)\n227\t\tif err != nil {\n228\t\t\treturn err\n229\t\t}\n230\t\n231\t\ts.stmtChunksBySource, err = db.Prepare(`\n232\t\t\tSELECT c.title, c.content, c.content_type, s.label, c.source_id\n233\t\t\tFROM chunks c\n234\t\t\tJOIN sources s ON s.id = c.source_id\n235\t\t\tWHERE c.source_id = ?\n236\t\t\tORDER BY c.rowid`)\n237\t\tif err != nil {\n238\t\t\treturn err\n239\t\t}\n240\t\n241\t\ts.stmtSourceChunkCount, err = db.Prepare(`\n242\t\t\tSELECT chunk_count FROM sources WHERE id = ?`)\n243\t\tif err != nil {\n244\t\t\treturn err\n245\t\t}\n246\t\n247\t\ts.stmtChunkContent, err = db.Prepare(`\n248\t\t\tSELECT content FROM chunks WHERE source_id = ?`)\n249\t\tif err != nil {\n250\t\t\treturn err\n251\t\t}\n252\t\n253\t\ts.stmtTrackAccess, err = db.Prepare(`\n254\t\t\tUPDATE sources SET last_accessed_at = datetime('now'), access_count = access_count + 1\n255\t\t\tWHERE id = ?`)\n256\t\tif err != nil {\n257\t\t\treturn err\n258\t\t}\n259\t\n260\t\treturn nil\n261\t}\n262\t\n263\t// Close finalizes statements, checkpoints WAL, and closes the database.\n264\t//\n265\t// WAL checkpoint architecture (see ADR-016):\n266\t//\n267\t// SQLite WAL mode creates sidecar files (.db-wal, .db-shm) that must be\n268\t// flushed into the main .db file before git operations — git only tracks the\n269\t// main file, and stale sidecars cause corruption on branch switches (ADR-015).\n270\t//\n271\t// Checkpoint requires exclusive WAL access. database/sql maintains a connection\n272\t// pool, and wal_checkpoint(TRUNCATE) silently degrades to passive (incomplete)\n273\t// if other pool connections hold the WAL open. To solve this:\n274\t//\n275\t//  1. Close all prepared statements\n276\t//  2. Close the connection pool (db.Close) — releases all WAL readers\n277\t//  3. Open a fresh single connection and run PRAGMA wal_checkpoint(TRUNCATE)\n278\t//\n279\t// This is the primary checkpoint mechanism. The CLI command `capy checkpoint`\n280\t// uses Checkpoint() which does step 3 standalone (for use when the server is\n281\t// not running). A git pre-commit hook calls `capy checkpoint` as a safety net.\n282\tfunc (s *ContentStore) Close() error {\n283\t\ts.mu.Lock()\n284\t\tdefer s.mu.Unlock()\n285\t\n286\t\tif s.db == nil {\n287\t\t\treturn nil\n288\t\t}\n289\t\n290\t\tstmts := []*sql.Stmt{\n291\t\t\ts.stmtInsertSource, s.stmtInsertChunk, s.stmtInsertTrigram,\n292\t\t\ts.stmtInsertVocab, s.stmtDeleteChunksBySource, s.stmtDeleteTrigramBySource,\n293\t\t\ts.stmtDeleteSource, s.stmtFindSourceByLabel, s.stmtUpdateSourceAccess,\n294\t\t\ts.stmtUpdateSourceKind, s.stmtFuzzyVocab, s.stmtGetSourceMeta,\n295\t\t\ts.stmtListSources, s.stmtChunksBySource,\n296\t\t\ts.stmtSourceChunkCount, s.stmtChunkContent, s.stmtTrackAccess,\n297\t\t}\n298\t\tfor _, stmt := range stmts {\n299\t\t\tif stmt != nil {\n300\t\t\t\tstmt.Close()\n301\t\t\t}\n302\t\t}\n303\t\n304\t\t// Close the connection pool FIRST. This releases all pooled connections\n305\t\t// that hold the WAL open. Without this, wal_checkpoint(TRUNCATE) can't\n306\t\t// get exclusive access and silently degrades to passive (incomplete).\n307\t\terr := s.db.Close()\n308\t\ts.db = nil\n309\t\n310\t\t// Now checkpoint with a fresh single connection — no other connections\n311\t\t// exist, so TRUNCATE gets exclusive access and fully flushes the WAL.\n312\t\tif cpErr := s.checkpoint(); cpErr != nil {\n313\t\t\tif err == nil {\n314\t\t\t\terr = cpErr\n315\t\t\t}\n316\t\t}\n317\t\n318\t\treturn err\n319\t}\n320\t\n321\t// checkpoint opens a dedicated single connection and runs\n322\t// PRAGMA wal_checkpoint(TRUNCATE). Must be called after the\n323\t// connection pool is closed so no other connections hold the WAL.\n324\tfunc (s *ContentStore) checkpoint() error {\n325\t\tdsn := s.dbPath + \"?_journal_mode=WAL&_busy_timeout=5000\"\n326\t\tdb, err := sql.Open(\"sqlite3\", dsn)\n327\t\tif err != nil {\n328\t\t\treturn err\n329\t\t}\n330\t\tdefer db.Close()\n331\t\tdb.SetMaxOpenConns(1)\n332\t\t_, err = db.Exec(\"PRAGMA wal_checkpoint(TRUNCATE)\")\n333\t\treturn err\n334\t}\n335\t\n336\tfunc (s *ContentStore) optimizeFTS(db *sql.DB) {\n337\t\tif _, err := db.Exec(\"INSERT INTO chunks(chunks) VALUES ('optimize')\"); err != nil {\n338\t\t\tslog.Warn(\"FTS5 optimize failed for chunks\", \"error\", err)\n339\t\t}\n340\t\tif _, err := db.Exec(\"INSERT INTO chunks_trigram(chunks_trigram) VALUES ('optimize')\"); err != nil {\n341\t\t\tslog.Warn(\"FTS5 optimize failed for chunks_trigram\", \"error\", err)\n342\t\t}\n343\t}\n344\t\n345\t// Checkpoint flushes the WAL into the main database file using a dedicated\n346\t// single connection (not the connection pool). This is the correct way to\n347\t// checkpoint from outside the running server — e.g., from `capy checkpoint`.\n348\tfunc (s *ContentStore) Checkpoint() error {\n349\t\tdsn := s.dbPath + \"?_journal_mode=WAL&_busy_timeout=5000\"\n350\t\tdb, err := sql.Open(\"sqlite3\", dsn)\n351\t\tif err != nil {\n352\t\t\treturn fmt.Errorf(\"opening database for checkpoint: %w\", err)\n353\t\t}\n354\t\tdefer db.Close()\n355\t\n356\t\t// Force a single connection — no pool interference.\n357\t\tdb.SetMaxOpenConns(1)\n358\t\n359\t\tvar busy, log, checkpointed int\n360\t\terr = db.QueryRow(\"PRAGMA wal_checkpoint(TRUNCATE)\").Scan(&busy, &log, &checkpointed)\n361\t\tif err != nil {\n362\t\t\treturn fmt.Errorf(\"checkpoint pragma failed: %w\", err)\n363\t\t}\n364\t\tif busy > 0 {\n365\t\t\treturn fmt.Errorf(\"checkpoint incomplete: %d pages busy (another process has the DB open)\", busy)\n366\t\t}\n367\t\n368\t\treturn nil\n369\t}\n370\t"}]},"uuid":"383d284d-8f65-4e42-8ab5-bf266be64f7a","timestamp":"2026-04-23T18:44:30.240Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/internal/store/store.go","content":"package store\n\nimport (\n\t\"context\"\n\t\"database/sql\"\n\t\"fmt\"\n\t\"log/slog\"\n\t\"os\"\n\t\"path/filepath\"\n\t\"sync\"\n\t\"sync/atomic\"\n\n\t_ \"github.com/mattn/go-sqlite3\"\n)\n\nconst fuzzyCacheMaxSize = 256\n\nconst optimizeEvery int64 = 50\n\nfunc (s *ContentStore) ctx() context.Context {\n\treturn context.Background()\n}\n\n// ContentStore manages the FTS5 knowledge base.\ntype ContentStore struct {\n\tdbPath      string\n\tprojectDir  string\n\ttitleWeight float64\n\n\tmu sync.Mutex\n\tdb *sql.DB\n\n\t// Prepared statements — indexing.\n\tstmtInsertSource          *sql.Stmt\n\tstmtInsertChunk           *sql.Stmt\n\tstmtInsertTrigram         *sql.Stmt\n\tstmtInsertVocab           *sql.Stmt\n\tstmtDeleteChunksBySource  *sql.Stmt\n\tstmtDeleteTrigramBySource *sql.Stmt\n\tstmtDeleteSource          *sql.Stmt\n\tstmtFindSourceByLabel     *sql.Stmt\n\tstmtUpdateSourceAccess    *sql.Stmt\n\tstmtUpdateSourceKind      *sql.Stmt\n\n\tinsertCount atomic.Int64\n\n\t// Fuzzy correction cache: nil value = \"no correction\"; key-missing = \"not cached\".\n\tfuzzyCacheMu sync.RWMutex\n\tfuzzyCache   map[string]*string\n\n\t// Prepared statements — search.\n\tstmtFuzzyVocab *sql.Stmt\n\n\t// Prepared statements — queries.\n\tstmtGetSourceMeta    *sql.Stmt\n\tstmtListSources      *sql.Stmt\n\tstmtChunksBySource   *sql.Stmt\n\tstmtSourceChunkCount *sql.Stmt\n\tstmtChunkContent     *sql.Stmt\n\tstmtTrackAccess      *sql.Stmt\n}\n\n// NewContentStore creates a new ContentStore. The database is not opened\n// until the first operation (lazy initialization via getDB).\n// titleWeight controls the BM25 title column weight; values <= 0 default to 2.0.\nfunc NewContentStore(dbPath, projectDir string, titleWeight float64) *ContentStore {\n\tif titleWeight <= 0 {\n\t\ttitleWeight = 2.0\n\t}\n\treturn &ContentStore{\n\t\tdbPath:      dbPath,\n\t\tprojectDir:  projectDir,\n\t\ttitleWeight: titleWeight,\n\t\tfuzzyCache:  make(map[string]*string),\n\t}\n}\n\n// getDB returns the database connection, initializing it on first call.\n// On corruption, it backs up the corrupt file and retries once.\nfunc (s *ContentStore) getDB() (*sql.DB, error) {\n\ts.mu.Lock()\n\tdefer s.mu.Unlock()\n\n\tif s.db != nil {\n\t\treturn s.db, nil\n\t}\n\n\tdbDir := filepath.Dir(s.dbPath)\n\tif err := os.MkdirAll(dbDir, 0o755); err != nil {\n\t\treturn nil, fmt.Errorf(\"creating DB directory: %w\", err)\n\t}\n\n\tif s.projectDir != \"\" {\n\t\t_ = os.WriteFile(filepath.Join(dbDir, \".project\"), []byte(s.projectDir+\"\\n\"), 0o644)\n\t}\n\n\tdb, err := s.openDB()\n\tif err != nil && isSQLiteCorruption(err) {\n\t\tslog.Warn(\"corrupt database detected, backing up and recreating\", \"path\", s.dbPath, \"error\", err)\n\t\tbackupCorruptDB(s.dbPath)\n\t\tdb, err = s.openDB()\n\t\tif err != nil {\n\t\t\treturn nil, fmt.Errorf(\"opening database after recovery: %w\", err)\n\t\t}\n\t}\n\tif err != nil {\n\t\treturn nil, err\n\t}\n\n\ts.db = db\n\treturn db, nil\n}\n\nfunc (s *ContentStore) openDB() (*sql.DB, error) {\n\tdsn := s.dbPath + \"?_journal_mode=WAL&_synchronous=NORMAL&_busy_timeout=5000&_foreign_keys=ON\"\n\tdb, err := sql.Open(\"sqlite3\", dsn)\n\tif err != nil {\n\t\treturn nil, fmt.Errorf(\"opening database: %w\", err)\n\t}\n\n\tif _, err := db.Exec(\"PRAGMA mmap_size = 268435456\"); err != nil {\n\t\tslog.Warn(\"failed to set mmap_size pragma\", \"error\", err)\n\t}\n\n\tif _, err := db.Exec(schemaSQL); err != nil {\n\t\tdb.Close()\n\t\treturn nil, fmt.Errorf(\"initializing schema: %w\", err)\n\t}\n\n\tif err := applyMigrations(db); err != nil {\n\t\tdb.Close()\n\t\treturn nil, fmt.Errorf(\"applying migrations: %w\", err)\n\t}\n\n\tif err := s.prepareStatements(db); err != nil {\n\t\tdb.Close()\n\t\treturn nil, fmt.Errorf(\"preparing statements: %w\", err)\n\t}\n\n\treturn db, nil\n}\n\nfunc (s *ContentStore) prepareStatements(db *sql.DB) error {\n\tvar err error\n\n\t// --- Indexing ---\n\n\ts.stmtInsertSource, err = db.Prepare(`\n\t\tINSERT INTO sources (label, content_type, chunk_count, code_chunk_count, content_hash, kind)\n\t\tVALUES (?, ?, ?, ?, ?, ?)`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtInsertChunk, err = db.Prepare(`\n\t\tINSERT INTO chunks (title, content, source_id, content_type)\n\t\tVALUES (?, ?, ?, ?)`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtInsertTrigram, err = db.Prepare(`\n\t\tINSERT INTO chunks_trigram (title, content, source_id, content_type)\n\t\tVALUES (?, ?, ?, ?)`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtInsertVocab, err = db.Prepare(`INSERT OR IGNORE INTO vocabulary (word) VALUES (?)`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtDeleteChunksBySource, err = db.Prepare(`DELETE FROM chunks WHERE source_id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtDeleteTrigramBySource, err = db.Prepare(`DELETE FROM chunks_trigram WHERE source_id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtDeleteSource, err = db.Prepare(`DELETE FROM sources WHERE id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtFindSourceByLabel, err = db.Prepare(`\n\t\tSELECT id, content_hash, kind FROM sources WHERE label = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtUpdateSourceAccess, err = db.Prepare(`\n\t\tUPDATE sources SET last_accessed_at = datetime('now') WHERE label = ? AND content_hash = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtUpdateSourceKind, err = db.Prepare(`\n\t\tUPDATE sources SET kind = ?, last_accessed_at = datetime('now') WHERE id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\t// --- Search ---\n\n\ts.stmtFuzzyVocab, err = db.Prepare(`\n\t\tSELECT word FROM vocabulary WHERE length(word) BETWEEN ? AND ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\t// --- Queries ---\n\n\ts.stmtGetSourceMeta, err = db.Prepare(`\n\t\tSELECT label, chunk_count, indexed_at, kind FROM sources WHERE label = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtListSources, err = db.Prepare(`\n\t\tSELECT id, label, content_type, chunk_count, code_chunk_count,\n\t\t\tindexed_at, last_accessed_at, access_count, content_hash, kind\n\t\tFROM sources ORDER BY id DESC`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtChunksBySource, err = db.Prepare(`\n\t\tSELECT c.title, c.content, c.content_type, s.label, c.source_id\n\t\tFROM chunks c\n\t\tJOIN sources s ON s.id = c.source_id\n\t\tWHERE c.source_id = ?\n\t\tORDER BY c.rowid`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtSourceChunkCount, err = db.Prepare(`\n\t\tSELECT chunk_count FROM sources WHERE id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtChunkContent, err = db.Prepare(`\n\t\tSELECT content FROM chunks WHERE source_id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\ts.stmtTrackAccess, err = db.Prepare(`\n\t\tUPDATE sources SET last_accessed_at = datetime('now'), access_count = access_count + 1\n\t\tWHERE id = ?`)\n\tif err != nil {\n\t\treturn err\n\t}\n\n\treturn nil\n}\n\n// Close finalizes statements, checkpoints WAL, and closes the database.\n//\n// WAL checkpoint architecture (see ADR-016):\n//\n// SQLite WAL mode creates sidecar files (.db-wal, .db-shm) that must be\n// flushed into the main .db file before git operations — git only tracks the\n// main file, and stale sidecars cause corruption on branch switches (ADR-015).\n//\n// Checkpoint requires exclusive WAL access. database/sql maintains a connection\n// pool, and wal_checkpoint(TRUNCATE) silently degrades to passive (incomplete)\n// if other pool connections hold the WAL open. To solve this:\n//\n//  1. Close all prepared statements\n//  2. Close the connection pool (db.Close) — releases all WAL readers\n//  3. Open a fresh single connection and run PRAGMA wal_checkpoint(TRUNCATE)\n//\n// This is the primary checkpoint mechanism. The CLI command `capy checkpoint`\n// uses Checkpoint() which does step 3 standalone (for use when the server is\n// not running). A git pre-commit hook calls `capy checkpoint` as a safety net.\nfunc (s *ContentStore) Close() error {\n\ts.mu.Lock()\n\tdefer s.mu.Unlock()\n\n\tif s.db == nil {\n\t\treturn nil\n\t}\n\n\tstmts := []*sql.Stmt{\n\t\ts.stmtInsertSource, s.stmtInsertChunk, s.stmtInsertTrigram,\n\t\ts.stmtInsertVocab, s.stmtDeleteChunksBySource, s.stmtDeleteTrigramBySource,\n\t\ts.stmtDeleteSource, s.stmtFindSourceByLabel, s.stmtUpdateSourceAccess,\n\t\ts.stmtUpdateSourceKind, s.stmtFuzzyVocab, s.stmtGetSourceMeta,\n\t\ts.stmtListSources, s.stmtChunksBySource,\n\t\ts.stmtSourceChunkCount, s.stmtChunkContent, s.stmtTrackAccess,\n\t}\n\tfor _, stmt := range stmts {\n\t\tif stmt != nil {\n\t\t\tstmt.Close()\n\t\t}\n\t}\n\n\t// Close the connection pool FIRST. This releases all pooled connections\n\t// that hold the WAL open. Without this, wal_checkpoint(TRUNCATE) can't\n\t// get exclusive access and silently degrades to passive (incomplete).\n\terr := s.db.Close()\n\ts.db = nil\n\n\t// Now checkpoint with a fresh single connection — no other connections\n\t// exist, so TRUNCATE gets exclusive access and fully flushes the WAL.\n\tif cpErr := s.checkpoint(); cpErr != nil {\n\t\tif err == nil {\n\t\t\terr = cpErr\n\t\t}\n\t}\n\n\treturn err\n}\n\n// checkpoint opens a dedicated single connection and runs\n// PRAGMA wal_checkpoint(TRUNCATE). Must be called after the\n// connection pool is closed so no other connections hold the WAL.\nfunc (s *ContentStore) checkpoint() error {\n\tdsn := s.dbPath + \"?_journal_mode=WAL&_busy_timeout=5000\"\n\tdb, err := sql.Open(\"sqlite3\", dsn)\n\tif err != nil {\n\t\treturn err\n\t}\n\tdefer db.Close()\n\tdb.SetMaxOpenConns(1)\n\t_, err = db.Exec(\"PRAGMA wal_checkpoint(TRUNCATE)\")\n\treturn err\n}\n\nfunc (s *ContentStore) optimizeFTS(db *sql.DB) {\n\tif _, err := db.Exec(\"INSERT INTO chunks(chunks) VALUES ('optimize')\"); err != nil {\n\t\tslog.Warn(\"FTS5 optimize failed for chunks\", \"error\", err)\n\t}\n\tif _, err := db.Exec(\"INSERT INTO chunks_trigram(chunks_trigram) VALUES ('optimize')\"); err != nil {\n\t\tslog.Warn(\"FTS5 optimize failed for chunks_trigram\", \"error\", err)\n\t}\n}\n\n// Checkpoint flushes the WAL into the main database file using a dedicated\n// single connection (not the connection pool). This is the correct way to\n// checkpoint from outside the running server — e.g., from `capy checkpoint`.\nfunc (s *ContentStore) Checkpoint() error {\n\tdsn := s.dbPath + \"?_journal_mode=WAL&_busy_timeout=5000\"\n\tdb, err := sql.Open(\"sqlite3\", dsn)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"opening database for checkpoint: %w\", err)\n\t}\n\tdefer db.Close()\n\n\t// Force a single connection — no pool interference.\n\tdb.SetMaxOpenConns(1)\n\n\tvar busy, log, checkpointed int\n\terr = db.QueryRow(\"PRAGMA wal_checkpoint(TRUNCATE)\").Scan(&busy, &log, &checkpointed)\n\tif err != nil {\n\t\treturn fmt.Errorf(\"checkpoint pragma failed: %w\", err)\n\t}\n\tif busy > 0 {\n\t\treturn fmt.Errorf(\"checkpoint incomplete: %d pages busy (another process has the DB open)\", busy)\n\t}\n\n\treturn nil\n}\n","numLines":370,"startLine":1,"totalLines":370}},"sourceToolAssistantUUID":"291b6f84-2ad2-4e13-bcd3-eeb9d94a357f","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"938b99c0-69d1-4db1-9a18-b8393d2d2afc","isSidechain":false,"promptId":"f8adf56b-c833-494e-b3b1-9ec5e17fe566","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01BzQ9teEU7EQgwxDLyWMbo3","type":"tool_result","content":"1\t# ADR-017: Separate ephemeral and durable sources in the knowledge store\n2\t\n3\t**Status:** Accepted\n4\t**Date:** 2026-04-15\n5\t**Supersedes:** Amends (but does not replace) ADR-006, ADR-007, ADR-011.\n6\t\n7\t## Context\n8\t\n9\tcapy is pitched as solving two problems: context-flood protection (§ADR-006) and persistent queryable memory (§ADR-007). These two jobs have opposite lifecycle requirements:\n10\t\n11\t| Role             | Wants                                                 | Examples                                   |\n12\t| ---------------- | ----------------------------------------------------- | ------------------------------------------ |\n13\t| Flood protection | Short-lived, aggressive cleanup, \"snapshot\" semantics | `git diff`, `find`, `ls`, API debug output |\n14\t| Long-term memory | Durable, accumulative, \"knowledge\" semantics          | fetched docs, curated indexed files        |\n15\t\n16\tBoth land in the same SQLite FTS5 store, searchable by the same `capy_search`, ranked by the same BM25, with only a free-form `label` string to separate them. The current code does not encode provenance or intended lifecycle anywhere in the schema.\n17\t\n18\t### Evidence the conflation bites in practice\n19\t\n20\t- `internal/store/schema.go:9-19` — the `sources` table has no source-kind column; `content_type` is just `plaintext|markdown|json` (see ADR-012), not a lifecycle hint.\n21\t- `internal/server/intent_search.go:17` — every `capy_execute`/`capy_execute_file` call with an `intent` parameter and >5 KB output auto-indexes the raw output into the persistent store. This is the dominant write path during normal sessions; ephemeral pollution is steady-state, not theoretical.\n22\t- `internal/store/cleanup.go:24-61` — `retentionScore` rewards code-density (pure code ⇒ `salience = 0.7`, same as a curated source file) and `cleanup.go:112` refuses to evict anything with `access_count > 0`. One intent-search hit makes an ephemeral row effectively immortal.\n23\t- `internal/server/tool_search.go:85` — search only filters by `Source` string. A `batch:git_diff,find,ls` chunk competes head-to-head against `https://react.dev/...` chunks in the same BM25 space.\n24\t- Labeling is inconsistent across write sites: `tool_execute.go:82` (`execute:<lang>`), `tool_execute_file.go:54` (`file:<path>`), `tool_batch.go:91` (`batch:<labels>`), `tool_fetch.go:48` (no prefix — raw URL or user string), `tool_index.go:48` (no prefix — user string or `indexed-content`). Ephemeral sources get prefixes; durable sources do not. Worse than no convention.\n25\t\n26\t### Why BM25 pollution is worse than it looks\n27\t\n28\tSQLite FTS5's BM25 relies on term frequency and inverse document frequency. A 10k-line `git diff` chunked into the index has very varied vocabulary and can mention a term like `authentication` dozens of times across modified files — inflating TF relative to a concise prose doc that mentions it twice. Even when the prose doc ranks first, having an ephemeral diff at position 2 or 3 still burns LLM context on noise. The cost compounds.\n29\t\n30\t## Decision\n31\t\n32\tIntroduce a **binary source-kind column** on the `sources` table:\n33\t\n34\t- `kind = 'ephemeral'` — transient command output captured for flood protection. Default-excluded from search. Cleaned up on a strict TTL (24h, configurable) regardless of `access_count`.\n35\t- `kind = 'durable'` — curated/fetched content intended as long-term memory. Default-included in search. Cleaned up by the existing retention-score policy (ADR-011).\n36\t\n37\tWrite sites are responsible for tagging at creation:\n38\t\n39\t| Write site                                                                     | `kind`      |\n40\t| ------------------------------------------------------------------------------ | ----------- |\n41\t| `tool_execute.go` (via `handleIntentOrReturn` → `intent_search.go`)            | `ephemeral` |\n42\t| `tool_execute_file.go` (via `handleIntentOrReturnWithSource`)                  | `ephemeral` |\n43\t| `tool_batch.go` (combined batch output)                                        | `ephemeral` |\n44\t| `tool_fetch.go` (HTTP-fetched content)                                         | `durable`   |\n45\t| `tool_index.go` (explicit user-authored or file-sourced index)                 | `durable`   |\n46\t\n47\tSearch (`tool_search.go`) default-excludes `ephemeral` unless the caller sets `include_kinds: [\"ephemeral\"]` (or `[\"durable\",\"ephemeral\"]`) OR passes an explicit `source:` filter that resolves to an ephemeral label. The array-shaped `include_kinds` is chosen over a `bool` so a future third kind can be added without a breaking change (see §Variants Considered #1). Intra-batch search (`tool_batch.go:124`) already uses `SourceMatchMode: \"exact\"` — this path is unaffected.\n48\t\n49\tCleanup (`cleanup.go`) splits into two code paths:\n50\t\n51\t1. `durable` sources — unchanged. `retentionScore`, `access_count = 0` gate, `evictableThreshold`.\n52\t2. `ephemeral` sources — pure TTL. `IndexedAt < now − TTL`. Access count is ignored. Default TTL 24 h, overridable via `.capy.toml`.\n53\t\n54\tMigration is one-shot on store open: `ALTER TABLE sources ADD COLUMN kind TEXT NOT NULL DEFAULT 'durable'`, then a retroactive `UPDATE` tagging rows whose label matches `execute:%`, `file:%`, `batch:%` as `ephemeral`. Existing durable rows stay durable by the default, matching the safety bias of ADR-011.\n55\t\n56\t## Variants Considered\n57\t\n58\t### 1. Three-kind taxonomy (`ephemeral | reference | note`)\n59\t\n60\tOriginally proposed during the analysis phase to distinguish fetched content (`reference`) from agent-authored summaries (`note`), anticipating a future authoring workflow (e.g., `capy_note` tool).\n61\t\n62\t**Dropped.** YAGNI — no authoring-specific tool exists, no cleanup policy differs between `reference` and `note`, and no search default differs between them. A third kind introduced today would be indistinguishable from `durable` in every code path. If an authoring workflow emerges with a distinct lifecycle, a third value can be added then. Binary is cheaper to reason about and to migrate.\n63\t\n64\t### 2. Second FTS5 virtual table for ephemeral content\n65\t\n66\tCreate `chunks_ephemeral` as a separate FTS5 table alongside `chunks` and `chunks_trigram`, then `UNION` at search time with a score penalty on ephemeral hits.\n67\t\n68\t**Dropped.** FTS5 BM25 scores are computed relative to the statistics of a single virtual table — IDF depends on the per-table corpus. A score of `2.5` in one table is not comparable to `2.5` in another. Merging and ranking across tables would require reimplementing global BM25 in application code, giving up the main reason we use FTS5 in the first place. The schema-column approach achieves the same result with a trivial `JOIN … WHERE kind = 'durable'` and preserves single-corpus BM25 semantics.\n69\t\n70\t### 3. Steeper temporal decay (`λ ≈ 0.3`) for ephemeral sources\n71\t\n72\tKeep the unified retention formula, but apply a much steeper `λ` (≈2-day half-life) to `ephemeral`.\n73\t\n74\t**Dropped.** This still fights the `access_count > 0` immortality gate in `cleanup.go:112`. An ephemeral row hit once by intent-search would still survive even with a steep decay, because `Cleanup()` short-circuits on `AccessCount > 0`. Strict TTL bypasses that gate cleanly and is simpler to reason about: \"ephemeral output older than N hours is gone.\" No probabilistic scoring needed for content whose useful life is measured in minutes to hours.\n75\t\n76\t### 4. Pure label-namespace convention (no schema change)\n77\t\n78\tEnforce prefix conventions (`execute:`, `batch:`, `file:`, `docs:`) everywhere and make `capy_search` apply a prefix-based filter.\n79\t\n80\t**Dropped.** The label is already overloaded (filter key + staleness hint + provenance + cleanup target — see the user-authored critique in the source of this ADR). Encoding lifecycle in a free-form string keeps all four concerns coupled and leaves the convention re-enforceable only by reviewing every write site. A schema column makes the contract machine-checkable and lets labels go back to being human-readable identifiers.\n81\t\n82\t### 5. Skip the FTS5 index entirely for ephemeral content\n83\t\n84\tStore ephemeral output in a separate plain table (no FTS) and scan linearly when needed.\n85\t\n86\t**Dropped.** `tool_batch.go:124` intra-batch search *does* need FTS5 (`SearchWithFallback` with `SourceMatchMode: \"exact\"`). Removing ephemeral from the index would require either reimplementing search for that table or giving up the batch-execute UX. The cost of keeping ephemeral in FTS5 (index churn on 24h-TTL rows) is bounded and acceptable for a local CLI — SQLite's WAL + periodic `VACUUM` (ADR-016) handle it.\n87\t\n88\t### 6. Aggressive cleanup flag on the existing unified policy\n89\t\n90\tAdd `capy_cleanup --aggressive` that ignores `access_count` and applies a shorter age threshold, keeping the unified policy otherwise.\n91\t\n92\t**Dropped as primary fix; may still ship as a manual escape hatch.** Aggressive cleanup requires the user to notice that pollution has accumulated and run the command. The design goal is that ephemeral data never becomes visible to default search in the first place. A manual flag is a reactive workaround, not a structural fix. (A `capy_cleanup --purge-ephemeral` convenience flag may still be useful operationally — see the design doc.)\n93\t\n94\t## Rationale\n95\t\n96\t- The schema column is the minimum change that encodes lifecycle as a machine-readable fact rather than a labeling convention. Everything else — search filter, cleanup split, stats split — follows trivially from having the column.\n97\t- Binary is enough for today and leaves room to add values later.\n98\t- Default-exclude-ephemeral-from-search matches the mental model users already have: they index docs to search them; they run commands to extract a specific summary now.\n99\t- TTL-based cleanup for ephemeral matches the mental model of a scratch cache.\n100\t- The migration is safe because existing rows default to `durable`, and the prefix-based retroactive `UPDATE` only downgrades rows that follow capy's own labeling convention.\n101\t\n102\t## Consequences\n103\t\n104\t**Positive**\n105\t\n106\t- `capy_search` returns signal over noise by default. Prose queries like \"authentication flow\" no longer compete with `git diff` hunks.\n107\t- Cleanup actually does its job. An intent-search on a 50 KB debug dump no longer produces a permanent KB resident.\n108\t- The `kind` column becomes a natural extension point for future lifecycle variants (manual notes, imported reference collections, etc.).\n109\t- `capy_stats` can report tier distribution split by kind, giving users an honest picture of what's in their KB.\n110\t\n111\t**Negative / trade-offs**\n112\t\n113\t- Schema change requires a one-shot migration. Mitigated by `ALTER TABLE … DEFAULT 'durable'` + retroactive `UPDATE` based on existing prefix convention — no user action required.\n114\t- Write-site tagging must be consistent going forward. Mitigated by making `kind` an argument to the `Index` method (not inferred from label), so any new write site is forced to decide.\n115\t- The intent-search path writes ephemeral data into the persistent DB, which feels wasteful but preserves the intra-session re-query use case (see design.md §Open question 1).\n116\t- Users who explicitly relied on ephemeral output surviving long-term (unlikely, but possible) lose that behavior. Mitigated by exposing `include_kinds` on `capy_search` and a configurable TTL.\n117\t\n118\t**Cross-reference**\n119\t\n120\t- ADR-006 (persistence) — unchanged.\n121\t- ADR-007 (tiered freshness + content-hash dedup) — `retentionScore` now applies only to `durable`; dedup still applies to both kinds.\n122\t- ADR-011 (conservative cleanup) — preserved for `durable`; explicitly *not* applied to `ephemeral`.\n123\t- ADR-012 (content-type internal only) — `kind` is *also* internal, following the same convention.\n124\t- ADR-016 (WAL + checkpoint) — index churn from 24 h TTL-eviction is expected to be handled by the existing WAL checkpoint cadence; no new knob required.\n125\t\n126\t## Release notes\n127\t\n128\tUser-facing bullets for the release that ships this ADR:\n129\t\n130\t- **Behavior change — `capy_search` default**: ephemeral sources (command output auto-indexed by `capy_execute`, `capy_execute_file`, and `capy_batch_execute`) are now excluded from search results by default. Prose queries no longer compete against `git diff` / `find` / `ls` output in BM25.\n131\t- **Recovery paths for intra-session re-query**: to include ephemeral rows, pass either\n132\t  - `include_kinds: [\"durable\",\"ephemeral\"]` (both) or `include_kinds: [\"ephemeral\"]` (ephemeral only), **or**\n133\t  - an explicit `source:` filter naming the ephemeral label prefix, e.g. `source: \"execute:shell\"`, `source: \"file:/abs/path\"`, or `source: \"batch:git_diff,find\"`. An explicit `source:` bypasses kind filtering.\n134\t\n135\t  The zero-results message from `capy_search` names both recovery paths when an ephemeral match exists but is excluded.\n136\t- **Automatic ephemeral TTL**: ephemeral sources are now purged 24 hours after indexing (configurable via `[store.cleanup] ephemeral_ttl_hours`; minimum 1). `access_count` is ignored — intent-search hits no longer extend ephemeral lifetime.\n137\t- **New `capy_cleanup purge_ephemeral` flag**: one-shot scratch clear that runs only the ephemeral TTL path and leaves durable rows untouched regardless of retention score.\n138\t- **Migration**: existing databases are migrated in place on first open. Rows with `execute:` / `file:` / `batch:` label prefixes are retroactively tagged `ephemeral`; all other rows stay `durable`. No user action required.\n139\t- **Stats**: `capy_stats` now reports a durable vs. ephemeral source breakdown, durable retention tiers (hot/warm/cold/evictable), and ephemeral TTL buckets (fresh/stale).\n140\t"}]},"uuid":"d7696cbd-8185-4bed-923b-d9887fbe8aa9","timestamp":"2026-04-23T18:44:30.241Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/docs/adr/017-source-kind-separation.md","content":"# ADR-017: Separate ephemeral and durable sources in the knowledge store\n\n**Status:** Accepted\n**Date:** 2026-04-15\n**Supersedes:** Amends (but does not replace) ADR-006, ADR-007, ADR-011.\n\n## Context\n\ncapy is pitched as solving two problems: context-flood protection (§ADR-006) and persistent queryable memory (§ADR-007). These two jobs have opposite lifecycle requirements:\n\n| Role             | Wants                                                 | Examples                                   |\n| ---------------- | ----------------------------------------------------- | ------------------------------------------ |\n| Flood protection | Short-lived, aggressive cleanup, \"snapshot\" semantics | `git diff`, `find`, `ls`, API debug output |\n| Long-term memory | Durable, accumulative, \"knowledge\" semantics          | fetched docs, curated indexed files        |\n\nBoth land in the same SQLite FTS5 store, searchable by the same `capy_search`, ranked by the same BM25, with only a free-form `label` string to separate them. The current code does not encode provenance or intended lifecycle anywhere in the schema.\n\n### Evidence the conflation bites in practice\n\n- `internal/store/schema.go:9-19` — the `sources` table has no source-kind column; `content_type` is just `plaintext|markdown|json` (see ADR-012), not a lifecycle hint.\n- `internal/server/intent_search.go:17` — every `capy_execute`/`capy_execute_file` call with an `intent` parameter and >5 KB output auto-indexes the raw output into the persistent store. This is the dominant write path during normal sessions; ephemeral pollution is steady-state, not theoretical.\n- `internal/store/cleanup.go:24-61` — `retentionScore` rewards code-density (pure code ⇒ `salience = 0.7`, same as a curated source file) and `cleanup.go:112` refuses to evict anything with `access_count > 0`. One intent-search hit makes an ephemeral row effectively immortal.\n- `internal/server/tool_search.go:85` — search only filters by `Source` string. A `batch:git_diff,find,ls` chunk competes head-to-head against `https://react.dev/...` chunks in the same BM25 space.\n- Labeling is inconsistent across write sites: `tool_execute.go:82` (`execute:<lang>`), `tool_execute_file.go:54` (`file:<path>`), `tool_batch.go:91` (`batch:<labels>`), `tool_fetch.go:48` (no prefix — raw URL or user string), `tool_index.go:48` (no prefix — user string or `indexed-content`). Ephemeral sources get prefixes; durable sources do not. Worse than no convention.\n\n### Why BM25 pollution is worse than it looks\n\nSQLite FTS5's BM25 relies on term frequency and inverse document frequency. A 10k-line `git diff` chunked into the index has very varied vocabulary and can mention a term like `authentication` dozens of times across modified files — inflating TF relative to a concise prose doc that mentions it twice. Even when the prose doc ranks first, having an ephemeral diff at position 2 or 3 still burns LLM context on noise. The cost compounds.\n\n## Decision\n\nIntroduce a **binary source-kind column** on the `sources` table:\n\n- `kind = 'ephemeral'` — transient command output captured for flood protection. Default-excluded from search. Cleaned up on a strict TTL (24h, configurable) regardless of `access_count`.\n- `kind = 'durable'` — curated/fetched content intended as long-term memory. Default-included in search. Cleaned up by the existing retention-score policy (ADR-011).\n\nWrite sites are responsible for tagging at creation:\n\n| Write site                                                                     | `kind`      |\n| ------------------------------------------------------------------------------ | ----------- |\n| `tool_execute.go` (via `handleIntentOrReturn` → `intent_search.go`)            | `ephemeral` |\n| `tool_execute_file.go` (via `handleIntentOrReturnWithSource`)                  | `ephemeral` |\n| `tool_batch.go` (combined batch output)                                        | `ephemeral` |\n| `tool_fetch.go` (HTTP-fetched content)                                         | `durable`   |\n| `tool_index.go` (explicit user-authored or file-sourced index)                 | `durable`   |\n\nSearch (`tool_search.go`) default-excludes `ephemeral` unless the caller sets `include_kinds: [\"ephemeral\"]` (or `[\"durable\",\"ephemeral\"]`) OR passes an explicit `source:` filter that resolves to an ephemeral label. The array-shaped `include_kinds` is chosen over a `bool` so a future third kind can be added without a breaking change (see §Variants Considered #1). Intra-batch search (`tool_batch.go:124`) already uses `SourceMatchMode: \"exact\"` — this path is unaffected.\n\nCleanup (`cleanup.go`) splits into two code paths:\n\n1. `durable` sources — unchanged. `retentionScore`, `access_count = 0` gate, `evictableThreshold`.\n2. `ephemeral` sources — pure TTL. `IndexedAt < now − TTL`. Access count is ignored. Default TTL 24 h, overridable via `.capy.toml`.\n\nMigration is one-shot on store open: `ALTER TABLE sources ADD COLUMN kind TEXT NOT NULL DEFAULT 'durable'`, then a retroactive `UPDATE` tagging rows whose label matches `execute:%`, `file:%`, `batch:%` as `ephemeral`. Existing durable rows stay durable by the default, matching the safety bias of ADR-011.\n\n## Variants Considered\n\n### 1. Three-kind taxonomy (`ephemeral | reference | note`)\n\nOriginally proposed during the analysis phase to distinguish fetched content (`reference`) from agent-authored summaries (`note`), anticipating a future authoring workflow (e.g., `capy_note` tool).\n\n**Dropped.** YAGNI — no authoring-specific tool exists, no cleanup policy differs between `reference` and `note`, and no search default differs between them. A third kind introduced today would be indistinguishable from `durable` in every code path. If an authoring workflow emerges with a distinct lifecycle, a third value can be added then. Binary is cheaper to reason about and to migrate.\n\n### 2. Second FTS5 virtual table for ephemeral content\n\nCreate `chunks_ephemeral` as a separate FTS5 table alongside `chunks` and `chunks_trigram`, then `UNION` at search time with a score penalty on ephemeral hits.\n\n**Dropped.** FTS5 BM25 scores are computed relative to the statistics of a single virtual table — IDF depends on the per-table corpus. A score of `2.5` in one table is not comparable to `2.5` in another. Merging and ranking across tables would require reimplementing global BM25 in application code, giving up the main reason we use FTS5 in the first place. The schema-column approach achieves the same result with a trivial `JOIN … WHERE kind = 'durable'` and preserves single-corpus BM25 semantics.\n\n### 3. Steeper temporal decay (`λ ≈ 0.3`) for ephemeral sources\n\nKeep the unified retention formula, but apply a much steeper `λ` (≈2-day half-life) to `ephemeral`.\n\n**Dropped.** This still fights the `access_count > 0` immortality gate in `cleanup.go:112`. An ephemeral row hit once by intent-search would still survive even with a steep decay, because `Cleanup()` short-circuits on `AccessCount > 0`. Strict TTL bypasses that gate cleanly and is simpler to reason about: \"ephemeral output older than N hours is gone.\" No probabilistic scoring needed for content whose useful life is measured in minutes to hours.\n\n### 4. Pure label-namespace convention (no schema change)\n\nEnforce prefix conventions (`execute:`, `batch:`, `file:`, `docs:`) everywhere and make `capy_search` apply a prefix-based filter.\n\n**Dropped.** The label is already overloaded (filter key + staleness hint + provenance + cleanup target — see the user-authored critique in the source of this ADR). Encoding lifecycle in a free-form string keeps all four concerns coupled and leaves the convention re-enforceable only by reviewing every write site. A schema column makes the contract machine-checkable and lets labels go back to being human-readable identifiers.\n\n### 5. Skip the FTS5 index entirely for ephemeral content\n\nStore ephemeral output in a separate plain table (no FTS) and scan linearly when needed.\n\n**Dropped.** `tool_batch.go:124` intra-batch search *does* need FTS5 (`SearchWithFallback` with `SourceMatchMode: \"exact\"`). Removing ephemeral from the index would require either reimplementing search for that table or giving up the batch-execute UX. The cost of keeping ephemeral in FTS5 (index churn on 24h-TTL rows) is bounded and acceptable for a local CLI — SQLite's WAL + periodic `VACUUM` (ADR-016) handle it.\n\n### 6. Aggressive cleanup flag on the existing unified policy\n\nAdd `capy_cleanup --aggressive` that ignores `access_count` and applies a shorter age threshold, keeping the unified policy otherwise.\n\n**Dropped as primary fix; may still ship as a manual escape hatch.** Aggressive cleanup requires the user to notice that pollution has accumulated and run the command. The design goal is that ephemeral data never becomes visible to default search in the first place. A manual flag is a reactive workaround, not a structural fix. (A `capy_cleanup --purge-ephemeral` convenience flag may still be useful operationally — see the design doc.)\n\n## Rationale\n\n- The schema column is the minimum change that encodes lifecycle as a machine-readable fact rather than a labeling convention. Everything else — search filter, cleanup split, stats split — follows trivially from having the column.\n- Binary is enough for today and leaves room to add values later.\n- Default-exclude-ephemeral-from-search matches the mental model users already have: they index docs to search them; they run commands to extract a specific summary now.\n- TTL-based cleanup for ephemeral matches the mental model of a scratch cache.\n- The migration is safe because existing rows default to `durable`, and the prefix-based retroactive `UPDATE` only downgrades rows that follow capy's own labeling convention.\n\n## Consequences\n\n**Positive**\n\n- `capy_search` returns signal over noise by default. Prose queries like \"authentication flow\" no longer compete with `git diff` hunks.\n- Cleanup actually does its job. An intent-search on a 50 KB debug dump no longer produces a permanent KB resident.\n- The `kind` column becomes a natural extension point for future lifecycle variants (manual notes, imported reference collections, etc.).\n- `capy_stats` can report tier distribution split by kind, giving users an honest picture of what's in their KB.\n\n**Negative / trade-offs**\n\n- Schema change requires a one-shot migration. Mitigated by `ALTER TABLE … DEFAULT 'durable'` + retroactive `UPDATE` based on existing prefix convention — no user action required.\n- Write-site tagging must be consistent going forward. Mitigated by making `kind` an argument to the `Index` method (not inferred from label), so any new write site is forced to decide.\n- The intent-search path writes ephemeral data into the persistent DB, which feels wasteful but preserves the intra-session re-query use case (see design.md §Open question 1).\n- Users who explicitly relied on ephemeral output surviving long-term (unlikely, but possible) lose that behavior. Mitigated by exposing `include_kinds` on `capy_search` and a configurable TTL.\n\n**Cross-reference**\n\n- ADR-006 (persistence) — unchanged.\n- ADR-007 (tiered freshness + content-hash dedup) — `retentionScore` now applies only to `durable`; dedup still applies to both kinds.\n- ADR-011 (conservative cleanup) — preserved for `durable`; explicitly *not* applied to `ephemeral`.\n- ADR-012 (content-type internal only) — `kind` is *also* internal, following the same convention.\n- ADR-016 (WAL + checkpoint) — index churn from 24 h TTL-eviction is expected to be handled by the existing WAL checkpoint cadence; no new knob required.\n\n## Release notes\n\nUser-facing bullets for the release that ships this ADR:\n\n- **Behavior change — `capy_search` default**: ephemeral sources (command output auto-indexed by `capy_execute`, `capy_execute_file`, and `capy_batch_execute`) are now excluded from search results by default. Prose queries no longer compete against `git diff` / `find` / `ls` output in BM25.\n- **Recovery paths for intra-session re-query**: to include ephemeral rows, pass either\n  - `include_kinds: [\"durable\",\"ephemeral\"]` (both) or `include_kinds: [\"ephemeral\"]` (ephemeral only), **or**\n  - an explicit `source:` filter naming the ephemeral label prefix, e.g. `source: \"execute:shell\"`, `source: \"file:/abs/path\"`, or `source: \"batch:git_diff,find\"`. An explicit `source:` bypasses kind filtering.\n\n  The zero-results message from `capy_search` names both recovery paths when an ephemeral match exists but is excluded.\n- **Automatic ephemeral TTL**: ephemeral sources are now purged 24 hours after indexing (configurable via `[store.cleanup] ephemeral_ttl_hours`; minimum 1). `access_count` is ignored — intent-search hits no longer extend ephemeral lifetime.\n- **New `capy_cleanup purge_ephemeral` flag**: one-shot scratch clear that runs only the ephemeral TTL path and leaves durable rows untouched regardless of retention score.\n- **Migration**: existing databases are migrated in place on first open. Rows with `execute:` / `file:` / `batch:` label prefixes are retroactively tagged `ephemeral`; all other rows stay `durable`. No user action required.\n- **Stats**: `capy_stats` now reports a durable vs. ephemeral source breakdown, durable retention tiers (hot/warm/cold/evictable), and ephemeral TTL buckets (fresh/stale).\n","numLines":140,"startLine":1,"totalLines":140}},"sourceToolAssistantUUID":"938b99c0-69d1-4db1-9a18-b8393d2d2afc","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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context7\\nUse this server to fetch current documentation whenever the user asks about a library, framework, SDK, API, CLI tool, or cloud service -- even well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. This includes API syntax, configuration, version migration, library-specific debugging, setup instructions, and CLI tool usage. Use even when you think you know the answer -- your training data may not reflect recent changes. Prefer this over web search for library docs.\\n\\nDo not use for: refactoring, writing scripts from scratch, debugging business logic, code review, or general programming concepts.\",\"## pal\\nWhen the user names a specific model (e.g. 'use chat with gpt5'), send that exact model in the tool call. When no model is mentioned, first use the `listmodels` tool from PAL to obtain available models to choose the best one from.\",\"## serena\\nYou have access to semantic coding tools upon which you rely heavily for all your work.\\nYou operate in a resource-efficient and intelligent manner, always keeping in mind to not read or generate\\ncontent that is not needed for the task at hand.\\n\\nSome tasks may require you to understand the architecture of large parts of the codebase, while for others,\\nit may be enough to read a small set of symbols or a single file.\\nYou avoid reading entire files unless it is absolutely necessary, instead relying on intelligent step-by-step \\nacquisition of information. Once you have read a full file, it does not make\\nsense to analyse it with the symbolic read tools; you already have the information.\\n\\nYou can achieve intelligent reading of code by using the symbolic tools for getting an overview of symbols and\\nthe relations between them, and then only reading the bodies of symbols that are necessary to complete the task at hand. \\nYou can use the standard tools like list_dir, find_file and search_for_pattern if you need to.\\nWhere appropriate, you pass the `relative_path` parameter to restrict the search to a specific file or directory.\\n\\nIf you are unsure about a symbol's name or location (to the extent that substring_matching for the symbol name is not enough), you can use the `search_for_pattern` tool, which allows fast\\nand flexible search for patterns in the codebase. In this way, you can first find candidates for symbols or files,\\nand then proceed with the symbolic tools.\\n\\n\\n\\nSymbols are identified by their `name_path` and `relative_path` (see the description of the `find_symbol` tool).\\nYou can get information about the symbols in a file by using the `get_symbols_overview` tool or use the `find_symbol` to search. \\nYou only read the bodies of symbols when you need to (e.g. if you want to fully understand or edit it).\\nFor example, if you are working with Python code and already know that you need to read the body of the constructor of the class Foo, you can directly\\nuse `find_symbol` with name path pattern `Foo/__init__` and `includ… 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bash ls\"},\"uuid\":\"a93d0369-8f72-454e-8829-2ebf1ebcf58d\",\"timestamp\":\"2026-04-05T12:06:26.214Z\",\"permissionMode\":\"default\",\"userType\":\"external\",\"entrypoint\":\"cli\",\"cwd\":\"/home/sergio/Projects/personal/capy\",\"sessionId\":\"102ad512-759a-43ad-8805-353ce341f65c\",\"version\":\"2.1.92\",\"gitBranch\":\"master\"}\n{\"parentUuid\":\"a93d0369-8f72-454e-8829-2ebf1ebcf58d\",\"isSidechain\":false,\"attachment\":{\"type\":\"deferred_tools_delta\",\"addedNames\":[\"AskUserQuestion\",\"CronCreate\",\"CronDelete\",\"CronList\",\"EnterPlanMode\",\"EnterWorktree\",\"ExitPlanMode\",\"ExitWorktree\",\"LSP\",\"ListMcpResourcesTool\",\"NotebookEdit\",\"ReadMcpResourceTool\",\"RemoteTrigger\",\"TaskCreate\",\"TaskGet\",\"TaskList\",\"TaskOutput\",\"TaskStop\",\"TaskUpdate\",\"WebFetch\",\"WebSearch\",\"mcp__capy__capy_batch_execute\",\"mcp__capy__capy_cleanup\",\"mcp__capy__capy_doctor\",\"mcp__capy__capy_execute\",\"mcp__capy__capy_execute_file\",\"mcp__capy__capy_fetch_and_index\",\"mcp__capy__capy_index\",\"mcp__capy__capy_search\",\"mcp__capy__capy_stats\",\"mcp__claude_ai_Gmail__authenticate\",\"mcp__claude_ai_Google_Calendar__authenticate\",\"mcp__claude_ai_HubSpot__authenticate\",\"mcp__claude_ai_Intercom__authenticate\",\"mcp__claude_ai_Linear__authenticate\",\"mcp__claude_ai_Notion__authenticate\",\"mcp__claude_ai_Slack__authenticate\",\"mcp__context7__query-docs\",\"mcp__context7__resolve-library-id\",\"mcp__pal__analyze\",\"mcp__pal__apilookup\",\"mcp__pal__challenge\",\"mcp__pal__chat\",\"mcp__pal__clink\",\"mcp__pal__codereview\",\"mcp__pal__consensus\",\"mcp__pal__debug\",\"mcp__pal__docgen\",\"mcp__pal__listmodels\",\"mcp__pal__planner\",\"mcp__pal__precommit\",\"mcp__pal__refactor\",\"mcp__pal__secaudit\",\"mcp__pal__testgen\",\"mcp__pal__thinkdeep\",\"mcp__pal__tracer\",\"mcp__pal__version\",\"mcp__serena__check_onboarding_performed\",\"mcp__serena__delete_memory\",\"mcp__serena__edit_memory\",\"mcp__serena__find_file\",\"mcp__serena__find_referencing_symbols\",\"mcp__serena__find_symbol\",\"mcp__serena__get_symbols_overview\",\"mcp__serena__initial_instructions\",\"mcp__serena__insert_after_symbol\",\"mcp__serena__insert_before_symbol\",\"mcp__serena__list_dir\",\"mcp__serena__list_memories\",\"mcp__serena__onboarding\",\"mcp__serena__open_dashboard\",\"mcp__serena__read_memory\",\"mcp__serena__rename_memory\",\"mcp__serena__rename_symbol\",\"mcp__serena__replace_symbol_body\",\"mcp__serena__safe_delete_symbol\",\"mcp__serena__search_for_pattern\",\"mcp__serena__write_memory\"],\"addedLines\":[\"AskUserQuestion\",\"CronCreate\",\"CronDelete\",\"CronList\",\"EnterPlanMode\",\"EnterWorktree\",\"ExitPlanMode\",\"ExitWorktree\",\"LSP\",\"ListMcpResourcesTool\",\"NotebookEdit\",\"ReadMcpResourceTool\",\"RemoteTrigger\",\"TaskCreate\",\"TaskGet\",\"TaskList\",\"TaskOutput\",\"TaskStop\",\"TaskUpdate\",\"WebFetch\",\"WebSearch\",\"mcp__capy__capy_batch_execute\",\"mcp__capy__capy_cleanup\",\"mcp__capy__capy_doctor\",\"mcp__capy__capy_execute\",\"mcp__capy__capy_execute_file\",\"mcp__capy__capy_fetch_and_index\",\"mcp__capy__capy_index\",\"mcp__capy__capy_search\",\"mcp__capy__capy_stats\",\"mcp__claude_ai_Gmail__authenticate\",\"mcp__claude_ai_Google_Calendar__authenticate\",\"mcp__claude_ai_HubSpot__authenticate\",\"mcp__claude_ai_Intercom__authenticate\",\"mcp__claude_ai_Linear__authenticate\",\"mcp__claude_ai_Notion__authenticate\",\"mcp__claude_ai_Slack__authenticate\",\"mcp__context7__query-docs\",\"mcp__context7__resolve-library-id\",\"mcp__pal__analyze\",\"mcp__pal__apilookup\",\"mcp__pal__challenge\",\"mcp__pal__chat\",\"mcp__pal__clink\",\"mcp__pal__codereview\",\"mcp__pal__consensus\",\"mcp__pal__debug\",\"mcp__pal__docgen\",\"mcp__pal__listmodels\",\"mcp__pal__planner\",\"mcp__pal__precommit\",\"mcp__pal__refactor\",\"mcp__pal__secaudit\",\"mcp__pal__testgen\",\"mcp__pal__thinkdeep\",\"mcp__pal__tracer\",\"mcp__pal__version\",\"mcp__serena__check_onboarding_performed\",\"mcp__serena__delete_memory\",\"mcp__serena__edit_memory\",\"mcp__serena__find_file\",\"mcp__serena__find_referencing_symbols\",\"mcp__serena__find_symbol\",\"mcp__serena__get_symbols_overview\",\"mcp__serena__initial_instructions\",\"mcp__serena__insert_after_symbol\",\"mcp__serena__insert_before_symbol\",\"mcp__serena__list_dir\",\"mcp__serena__list_memories\",\"mcp__serena__onboarding\",\"mcp__serena__open_dashboard\",\"mcp__serena__read_memory\",\"mcp__serena__rename_memory\",\"mcp__serena__rename_symbol\",\"mcp__serena__replace_symbol_body\",\"mcp__serena__safe_delete_symbol\",\"mcp__serena__search_for_pattern\",\"mcp__serena__write_memory\"],\"removedNames\":[]},\"type\":\"attachment\",\"uuid\":\"5e247214-c02f-4da2-bb29-959138b04965\",\"timestamp\":\"2026-04-05T12:06:26.214Z\",\"userType\":\"external\",\"entrypoint\":\"cli\",\"cwd\":\"/home/sergio/Projects/personal/capy\",\"sessionId\":\"102ad512-759a-43ad-8805-353ce341f65c\",\"version\":\"2.1.92\",\"gitBranch\":\"master\"}\n{\"parentUuid\":\"5e247214-c02f-4da2-bb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context7\\nUse this server to fetch current documentation whenever the user asks about a library, framework, SDK, API, CLI tool, or cloud service -- even well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. This includes API syntax, configuration, version migration, library-specific debugging, setup instructions, and CLI tool usage. Use even when you think you know the answer -- your training data may not reflect recent changes. Prefer this over web search for library docs.\\n\\nDo not use for: refactoring, writing scripts from scratch, debugging business logic, code review, or general programming concepts.\",\"## pal\\nWhen the user names a specific model (e.g. 'use chat with gpt5'), send that exact model in the tool call. When no model is mentioned, first use the `listmodels` tool from PAL to obtain available models to choose the best one from.\",\"## serena\\nYou have access to semantic coding tools upon which you rely heavily for all your work.\\nYou operate in a resource-efficient and intelligent manner, always keeping in mind to not read or generate\\ncontent that is not needed for the task at hand.\\n\\nSome tasks may require you to understand the architecture of large parts of the codebase, while for others,\\nit may be enough to read a small set of symbols or a single file.\\nYou avoid reading entire files unless it is absolutely necessary, instead relying on intelligent step-by-step \\nacquisition of information. Once you have read a full file, it does not make\\nsense to analyse it with the symbolic read tools; you already have the information.\\n\\nYou can achieve intelligent reading of code by using the symbolic tools for getting an overview of symbols and\\nthe relations between them, and then only reading the bodies of symbols that are necessary to complete the task at hand. \\nYou can use the standard tools like list_dir, find_file and search_for_pattern if you need to.\\nWhere appropriate, you pass the `relative_path` parameter to restrict the search to a specific file or directory.\\n\\nIf you are unsure about a symbol's name or location (to the extent that substring_matching for the symbol name is not enough), you can use the `search_for_pattern` tool, which allows fast\\nand flexible search for patterns in the codebase. In this way, you can first find candidates for symbols or files,\\nand then proceed with the symbolic tools.\\n\\n\\n\\nSymbols are identified by their `name_path` and `relative_path` (see the description of the `find_symbol` tool).\\nYou can get information about the symbols in a file by using the `get_symbols_overview` tool or use the `find_symbol` to search. \\nYou only read the bodies of symbols when you need to (e.g. if you want to fully understand or edit it).\\nFor example, if you are working with Python code and already know that you need to read the body of the constructor of the class Foo, you can directly\\nuse `find_symbol` with name path pattern `Foo/__init__` and `includ… [truncated]\"],\"removedNames\":[]},\"type\":\"attachment\",\"uuid\":\"36983bd2-534a-4d43-9c7e-51eac81a53e6\",\"timestamp\":\"2026-04-05T12:06:26.214Z\",\"userType\":\"external\",\"entrypoint\":\"cli\",\"cwd\":\"/home/sergio/Projects/personal/capy\",\"sessionId\":\"102ad512-759a-43ad-8805-353ce341f65c\",\"version\":\"2.1.92\",\"gitBranch\":\"master\"}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"0a0b4c05-daa9-452d-8bd4-eb5e3144ab78","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"type":"permission-mode","permissionMode":"default","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"333ad2e1-923d-4b22-85ae-0e2594150a5a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_018KtosH2o79NSpvKgpR5Lga","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Wr9P7MzTEY1BXN1oj5ajZM","name":"Bash","input":{"command":"cat ~/.claude/projects/-home-sergio-Projects-personal-capy/102ad512-759a-43ad-8805-353ce341f65c.jsonl | python3 -c \"\nimport json, sys, collections\ntypes = collections.Counter()\nfor line in sys.stdin:\n    obj = json.loads(line)\n    t = obj.get('type', 'unknown')\n    types[t] += 1\nfor t, c in types.most_common():\n    print(f'{c:4d}  {t}')\n\"","description":"Count message types in a session file"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3599,"cache_read_input_tokens":81242,"output_tokens":205,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3599,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMChXhSzvE2nUHiT8pTr","type":"assistant","uuid":"e32c5a05-85f0-4bca-9c06-18cf1a17f060","timestamp":"2026-04-23T18:48:29.358Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"e32c5a05-85f0-4bca-9c06-18cf1a17f060","isSidechain":false,"promptId":"5f6eab81-2d82-4829-82dd-585d893cf588","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Wr9P7MzTEY1BXN1oj5ajZM","type":"tool_result","content":"  10  assistant\n   6  user\n   3  file-history-snapshot\n   2  permission-mode\n   2  attachment\n   1  last-prompt","is_error":false}]},"uuid":"10810a28-eda6-4ae7-a3dc-57798f53a9fa","timestamp":"2026-04-23T18:48:31.963Z","toolUseResult":{"stdout":"  10  assistant\n   6  user\n   3  file-history-snapshot\n   2  permission-mode\n   2  attachment\n   1  last-prompt","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"e32c5a05-85f0-4bca-9c06-18cf1a17f060","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"10810a28-eda6-4ae7-a3dc-57798f53a9fa","isSidechain":false,"attachment":{"type":"task_reminder","content":[],"itemCount":0},"type":"attachment","uuid":"16fdbdb3-1a75-43fb-9d0e-b74b5f69ae00","timestamp":"2026-04-23T18:48:31.971Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"16fdbdb3-1a75-43fb-9d0e-b74b5f69ae00","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_016Mvvm9XGh57aK3TKii7JL3","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01FW9PHVvyXJuvmNvpS1xNMC","name":"Bash","input":{"command":"cat ~/.claude/projects/-home-sergio-Projects-personal-capy/102ad512-759a-43ad-8805-353ce341f65c.jsonl | python3 -c \"\nimport json, sys\nfor line in sys.stdin:\n    obj = json.loads(line)\n    t = obj.get('type', 'unknown')\n    if t == 'user':\n        msg = obj.get('message', {})\n        content = msg.get('content', '')\n        if isinstance(content, str):\n            print(f'USER (str): {content[:120]}')\n        elif isinstance(content, list):\n            for block in content:\n                btype = block.get('type', '?')\n                if btype == 'text':\n                    print(f'USER (text block): {block[\\\"text\\\"][:120]}')\n                else:\n                    print(f'USER ({btype} block)')\n    elif t == 'assistant':\n        msg = obj.get('message', {})\n        content = msg.get('content', [])\n        if isinstance(content, str):\n            print(f'ASST (str): {content[:120]}')\n        elif isinstance(content, list):\n            for block in content:\n                btype = block.get('type', '?')\n                if btype == 'text':\n                    print(f'ASST (text): {block[\\\"text\\\"][:120]}')\n                elif btype == 'tool_use':\n                    print(f'ASST (tool_use): {block.get(\\\"name\\\", \\\"?\\\")}')\n                elif btype == 'tool_result':\n                    print(f'ASST (tool_result)')\n                else:\n                    print(f'ASST ({btype})')\n\"","description":"Show message structure in session"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":363,"cache_read_input_tokens":84841,"output_tokens":506,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":363,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCi3tQQNT2gMN5LyZCK","type":"assistant","uuid":"809c32d1-47ad-4afe-9684-b187d40f547e","timestamp":"2026-04-23T18:48:39.597Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"809c32d1-47ad-4afe-9684-b187d40f547e","isSidechain":false,"promptId":"5f6eab81-2d82-4829-82dd-585d893cf588","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FW9PHVvyXJuvmNvpS1xNMC","type":"tool_result","content":"USER (str): run bash ls\nASST (thinking)\nASST (tool_use): Bash\nUSER (tool_result block)\nASST (text): \n\nHere's the project root contents:\n\n| Entry | Type |\n|-------|------|\n| `agentmemory/` | Directory |\n| `capy/` | Direct\nUSER (str): run git diff between head and root\nASST (thinking)\nASST (text): This diff will be very large (entire codebase history), so I'll run it in the capy sandbox to avoid flooding context.\nASST (tool_use): ToolSearch\nUSER (tool_result block)\nASST (tool_use): mcp__capy__capy_batch_execute\nUSER (tool_result block)\nASST (text): Here's the summary of the diff from root commit (`e7ab4a0`) to HEAD (`6dbe372`):\n\n**Root → HEAD diff stats** (3,187 line\nUSER (str): where did you get the project definition \"an MCP server for context window reduction.\"? It's also an LLM persistent memo\nASST (thinking)\nASST (text): You're right — I pulled that from `CLAUDE.md` which says:\n\n> `capy` is an MCP (Model Context Protocol) server and Claude","is_error":false}]},"uuid":"bc5cccd0-5276-4e24-8c8a-378951c1cd88","timestamp":"2026-04-23T18:48:41.264Z","toolUseResult":{"stdout":"USER (str): run bash ls\nASST (thinking)\nASST (tool_use): Bash\nUSER (tool_result block)\nASST (text): \n\nHere's the project root contents:\n\n| Entry | Type |\n|-------|------|\n| `agentmemory/` | Directory |\n| `capy/` | Direct\nUSER (str): run git diff between head and root\nASST (thinking)\nASST (text): This diff will be very large (entire codebase history), so I'll run it in the capy sandbox to avoid flooding context.\nASST (tool_use): ToolSearch\nUSER (tool_result block)\nASST (tool_use): mcp__capy__capy_batch_execute\nUSER (tool_result block)\nASST (text): Here's the summary of the diff from root commit (`e7ab4a0`) to HEAD (`6dbe372`):\n\n**Root → HEAD diff stats** (3,187 line\nUSER (str): where did you get the project definition \"an MCP server for context window reduction.\"? It's also an LLM persistent memo\nASST (thinking)\nASST (text): You're right — I pulled that from `CLAUDE.md` which says:\n\n> `capy` is an MCP (Model Context Protocol) server and Claude","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"809c32d1-47ad-4afe-9684-b187d40f547e","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"bc5cccd0-5276-4e24-8c8a-378951c1cd88","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_014BcDZyWgwedTnL6rBf45Qg","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"ErMCClkIDRgCKkBuYwQv8g1bZUaHkobOMTuoxs8l1HwKZv1APrVA8QG/9sk8kzYeQvBzDvnHYC2oLWDN7mWAWm8CehXOQRw9lGFDMg9jbGF1ZGUtb3B1cy00LTY4ABIMBK0RxE0LhUc64NqeGgx0HPSsyIvUHY0RHnoiME4Lmntx8V8Daw6mwXmc7gETeHcbBvKLuMYp9FRakjlJXtb30OxftsHBf+sL2R7fUCqHAZKsZm9oYDoenWXurLb1neAEggZjhPF+eqmlZEEwEHDwdu0TYdzLjkcdKioHk/mNYmQdUplVUNMe1lK0rVby1vZHk54VHSwb9kffBNfd6bh2JZDAtVMqgPnpTc+lgqnDh4O9jeXJL2PmTYmDQKKtuPt4Z1iHRH0BDVEZXLEY2+CDXTxzN0BALhgB"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":833,"cache_read_input_tokens":85204,"output_tokens":375,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":833,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCija6swY1DNh26A7e9","type":"assistant","uuid":"87c45ab6-dd21-45ad-950e-31cb610693d7","timestamp":"2026-04-23T18:48:44.479Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"87c45ab6-dd21-45ad-950e-31cb610693d7","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_014BcDZyWgwedTnL6rBf45Qg","type":"message","role":"assistant","content":[{"type":"text","text":"Good, now I understand the format. Key observations:\n\n- **Directory naming**: Claude Code uses path-based names (not hashes) like `-home-sergio-Projects-personal-capy`\n- **Message types**: `user`, `assistant`, `attachment`, `file-history-snapshot`, `permission-mode`, `last-prompt`\n- **User messages**: `content` can be a string or array of blocks (`text`, `tool_result`)\n- **Assistant messages**: `content` is an array of blocks (`text`, `thinking`, `tool_use`)\n- **Non-JSONL entries**: Some UUIDs have bare directories (not `.jsonl`) alongside them\n\nThis changes the session discovery approach. The directory is NOT hash-based — it's a path-mangled name. So we can't use `ProjectHash()` to find it.\n\n**Question 3:** How should we resolve the session directory? Two options:\n\n**A.** Derive it the same way Claude Code does — replace `/` with `-` in the absolute project path and look in `~/.claude/projects/`. I can reverse-engineer the exact mangling from the directory names we just saw.\n\n**B.** Accept the session directory path as a config option in `.capy.toml`, with auto-detection as default.\n\nI'd go with **A** (auto-detection only) — it's deterministic and adding config for it is premature. If Claude Code changes its naming convention, we update the detection. Does that work?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":833,"cache_read_input_tokens":85204,"output_tokens":375,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":833,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCija6swY1DNh26A7e9","type":"assistant","uuid":"fdec26c0-fbd6-476f-8e34-444b13458063","timestamp":"2026-04-23T18:48:52.793Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"fdec26c0-fbd6-476f-8e34-444b13458063","isSidechain":false,"type":"system","subtype":"turn_duration","durationMs":34106,"messageCount":148,"timestamp":"2026-04-23T18:48:52.862Z","uuid":"30241461-0f83-4bc4-85b4-ee423dac2b60","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"file-history-snapshot","messageId":"dd7aa374-6a9c-44d4-bef1-429b6564d1a6","snapshot":{"messageId":"dd7aa374-6a9c-44d4-bef1-429b6564d1a6","trackedFileBackups":{},"timestamp":"2026-04-23T18:51:38.779Z"},"isSnapshotUpdate":false}
 {"parentUuid":"30241461-0f83-4bc4-85b4-ee423dac2b60","isSidechain":false,"promptId":"5cd2c3be-0851-4a69-8596-51b5837f4f0f","type":"user","message":{"role":"user","content":"We can go with auto-detection, but we need to consider one of capy's philosophies - sharable knowledge via commitable knowledge.db. Different OSes will have different paths for the same project. Different people might have the project commited in different directories. We need to solve this problem otherwise we break the \"sharable\" part of capy"},"uuid":"dd7aa374-6a9c-44d4-bef1-429b6564d1a6","timestamp":"2026-04-23T18:51:38.757Z","permissionMode":"default","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"dd7aa374-6a9c-44d4-bef1-429b6564d1a6","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AZj1ZEdxTh4cTAhFoU21Et","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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 {"parentUuid":"88c72ce7-8e20-48aa-be15-3808e2ab7a88","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01AZj1ZEdxTh4cTAhFoU21Et","type":"message","role":"assistant","content":[{"type":"text","text":"That's a sharp catch. You're right — the session directory path is machine-specific (`-home-sergio-...` vs `-home-alice-code-...`), so if we bake paths into labels or rely on path-based discovery assumptions, the committed knowledge.db becomes non-portable.\n\nThe fix is to separate the two concerns:\n\n1. **Discovery** (finding session files) — inherently local. Only works on the machine where sessions exist. Path derivation lives here and never leaks into the DB.\n\n2. **Labels** (what gets stored in the DB) — must be path-agnostic. Use the session UUID, not the file path: `session:102ad512-759a-43ad-8805-353ce341f65c`. The UUID is universally unique and not tied to any machine or directory structure.\n\nThis way:\n- Machine A indexes its sessions with UUID-based labels, commits the DB\n- Machine B pulls the DB, gets all of A's session knowledge — searchable immediately\n- Machine B scans its own local session directory (different path, different sessions), indexes its own sessions with their own UUIDs — no collisions, no conflicts\n- The mtime gate is a local-only optimization — on a fresh machine with a shared DB, the content_hash dedup still prevents re-indexing identical content\n\nThe only open question: if the same person uses the same project on two machines (say laptop + desktop), different sessions produce different UUIDs anyway, so there's no conflict.\n\n**Question 4:** Does the `session:` label prefix convention work for you, or do you want something richer (e.g. including the session date)?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":449,"cache_read_input_tokens":86037,"output_tokens":1439,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":449,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMCwpZMfY4yANw6H76EY","type":"assistant","uuid":"5de6e46e-4144-49ba-85f4-3781c3582695","timestamp":"2026-04-23T18:52:16.547Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"5de6e46e-4144-49ba-85f4-3781c3582695","isSidechain":false,"type":"system","subtype":"turn_duration","durationMs":37830,"messageCount":152,"timestamp":"2026-04-23T18:52:16.609Z","uuid":"04341dc2-ab4a-45fa-b602-19764950344e","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"69118ca8-cca3-40e8-ba14-2eddd7e99719","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_018uEh4RpBspB4t1CnsGpatC","type":"message","role":"assistant","content":[{"type":"text","text":"Makes sense. Label format: `session:2026-04-05:102ad512-759a-43ad-8805-353ce341f65c` — date first for chronological sorting, full UUID for uniqueness. The date comes from the first user message timestamp in the JSONL.\n\nCombined with the chunk title format we already agreed on (`Session 2026-04-05 | Turns 1-4 | Tools: Bash, Edit`), this gives you two levels of chronological ordering: session-level from the label, turn-level from the chunk title.\n\nA search for `source: \"session:\"` returns all session chunks, sorted by date. A search for `source: \"session:2026-04\"` narrows to April 2026. The existing LIKE-based source filter already supports this.\n\n**Question 5 (last one):**\n\nFor stats reporting in `capy_stats` — session sources need their own section alongside durable and ephemeral. The current stats struct has `DurableSourceCount`, `EphemeralSourceCount`, and tier breakdowns for each.\n\nFor sessions, I'd add `SessionSourceCount` and two TTL buckets mirroring ephemeral: `SessionFreshCount` (within TTL) and `SessionStaleCount` (past TTL, awaiting cleanup). No retention tiers since sessions use strict TTL.\n\nStraightforward enough, or do you want something different in the stats view?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1466,"cache_read_input_tokens":86486,"output_tokens":687,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1466,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMDAtuuRJBq5yZ3ZFned","type":"assistant","uuid":"afb1d6ac-15c2-4809-babe-c1c7d9beb91c","timestamp":"2026-04-23T18:54:52.649Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"ccdc3acd-8f7f-4f1e-adeb-71a71f1eb9d8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01EN6PhrRTa4xYu59TvB6Bps","type":"message","role":"assistant","content":[{"type":"text","text":"Good, all decisions are locked. Moving to Step 4 — I'll describe the design in sections, asking for confirmation after each.\n\n```\nTask Progress:\n- [x] Step 1: Understand the current state of the project\n- [x] Step 2: Check the documentation\n- [x] Step 3: Help refine the idea/feature\n- [ ] Step 4: Describe the design\n- [ ] Step 5: Document the design\n- [ ] Step 6: Create the task list\n```\n\n---\n\n**Section 1: Overview and Problem Statement**\n\nClaude Code stores conversation sessions as JSONL files in `~/.claude/projects/<project-dir-name>/`. These sessions contain valuable decisions, rationale, and context that is currently lost after conversations end. capy already solves context flooding and provides persistent queryable memory, but only for content explicitly indexed during a session — the conversations themselves are invisible to future searches.\n\nSessionflow RAG makes past sessions automatically searchable by indexing their human/assistant text content into capy's FTS5 knowledge base. A background sweep runs at MCP server startup, parsing session JSONL files, filtering out noise (tool results, system messages, trivial sessions), chunking the conversational text into BM25-friendly windows, and indexing them under a new `KindSession` source kind. Sessions are included in default search results and have a configurable TTL (default 60 days) to preserve \"progress over time\" for the project.\n\nThe feature is entirely automatic — no MCP tool is exposed, the assistant never needs to think about it, and the indexed content stays portable across machines by using machine-agnostic labels (session UUID + date, not file paths).\n\n---\n\nDoes this overview capture it correctly?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":700,"cache_read_input_tokens":87952,"output_tokens":527,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":700,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMDGyJFJDuFYLikEiGyo","type":"assistant","uuid":"f43e59a7-b659-4e3a-b817-b8ed7e5d7c0e","timestamp":"2026-04-23T18:56:14.894Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"f43e59a7-b659-4e3a-b817-b8ed7e5d7c0e","isSidechain":false,"promptId":"8608274f-f62b-4227-9eb8-8d72a6835fce","type":"user","message":{"role":"user","content":"yes, but maybe date+time is better?"},"uuid":"f59332f8-3e22-485a-9091-a063c1ced7c1","timestamp":"2026-04-23T18:58:18.928Z","permissionMode":"default","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"f59332f8-3e22-485a-9091-a063c1ced7c1","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_0117HtBsaDmTXWUkeBPT8DBy","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":547,"cache_read_input_tokens":88652,"output_tokens":536,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":547,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMDTKQkWZpvLbxN9WmRy","type":"assistant","uuid":"78b1a8eb-749b-4870-9ddc-8eacac74eff1","timestamp":"2026-04-23T18:58:22.853Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"78b1a8eb-749b-4870-9ddc-8eacac74eff1","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_0117HtBsaDmTXWUkeBPT8DBy","type":"message","role":"assistant","content":[{"type":"text","text":"Agreed — `session:2026-04-05T12:06:26Z:102ad512-759a-43ad-8805-353ce341f65c`. Multiple sessions per day should be orderable. Updated.\n\n---\n\n**Section 2: Session File Parsing and Filtering**\n\nSession JSONL files contain one JSON object per line. Each line has a `type` field: `user`, `assistant`, `attachment`, `file-history-snapshot`, `permission-mode`, `last-prompt`. Only `user` and `assistant` types carry conversation content.\n\n**User messages** have `message.content` as either a plain string or an array of content blocks. We extract only string content and `{\"type\": \"text\"}` blocks. `tool_result` blocks are dropped entirely — they contain raw tool output (file contents, command output) that would pollute BM25 term frequencies. Human messages starting with `/` (slash commands like `/config`, `/compact`, `/help`) are skipped.\n\n**Assistant messages** have `message.content` as an array of blocks. We extract `{\"type\": \"text\"}` blocks only. `tool_use` blocks are not included in the transcript text, but we extract the `name` field from each for metadata (tool names appear in chunk titles for searchability). `thinking` blocks are skipped — they're internal reasoning and not part of the visible conversation.\n\n**Compact summaries** — when Claude Code compacts a conversation, the resulting summary message is dense, high-signal assistant text. These are kept and treated as regular assistant text. They're excellent for BM25.\n\n**Session-level gate**: after filtering, a session must have at least 2 meaningful turn pairs (human + assistant text response) AND at least 200 characters of total assistant text. Sessions that don't pass are skipped entirely — this catches config-only sessions, quick one-off commands, and aborted conversations.\n\n---\n\nSound right?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":547,"cache_read_input_tokens":88652,"output_tokens":536,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":547,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMDTKQkWZpvLbxN9WmRy","type":"assistant","uuid":"4c419bf6-e632-4896-9199-e2c8b17f3665","timestamp":"2026-04-23T18:58:33.477Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"4c419bf6-e632-4896-9199-e2c8b17f3665","isSidechain":false,"type":"system","subtype":"away_summary","content":"We're designing sessionflow RAG to auto-index Claude Code session transcripts into capy's FTS5 knowledge base. Currently walking through the design section by section for approval — next up is your confirmation on the session parsing and filtering rules I just described. (disable recaps in /config)","timestamp":"2026-04-23T19:01:38.254Z","uuid":"1f134624-333d-47d7-8447-804f8dbf486c","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"e3175935-465a-4163-8c20-c4e80c8d3f1a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"text","text":"Launching 10 exploration agents across both project directories to build a complete picture of the JSONL format."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"cd66660b-5ce8-40f4-9d02-d1cff6ce3b78","timestamp":"2026-04-23T19:13:21.143Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"cd66660b-5ce8-40f4-9d02-d1cff6ce3b78","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Jc216enu4HTqt8eFqJKK2L","name":"Agent","input":{"description":"Session types catalog (capy)","subagent_type":"Explore","prompt":"Analyze ALL .jsonl session files in ~/.claude/projects/-home-sergio-Projects-personal-capy/\n\nFor each file, parse every line as JSON and collect:\n1. Every unique `type` field value\n2. For each type, count how many times it appears across all files\n3. For types \"user\" and \"assistant\", also collect every unique content block `type` (e.g. \"text\", \"tool_use\", \"tool_result\", \"thinking\", \"image\", etc.)\n\nUse a Python script via Bash to process all files at once. Report the complete taxonomy of types and content block types with counts. Be thorough — don't sample, process every file.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"3867f770-a9d6-4571-a189-fb06a51d926c","timestamp":"2026-04-23T19:13:25.200Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"3867f770-a9d6-4571-a189-fb06a51d926c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JcfzaM6xRJ8ruTbLiBGnu5","name":"Agent","input":{"description":"Session types catalog (toolbox)","subagent_type":"Explore","prompt":"Analyze ALL .jsonl session files in ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nFor each file, parse every line as JSON and collect:\n1. Every unique `type` field value\n2. For each type, count how many times it appears across all files\n3. For types \"user\" and \"assistant\", also collect every unique content block `type` (e.g. \"text\", \"tool_use\", \"tool_result\", \"thinking\", \"image\", etc.)\n\nUse a Python script via Bash to process all files at once. Report the complete taxonomy of types and content block types with counts. Be thorough — don't sample, process every file.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"bd25f7a2-9ecb-4f3f-9165-0b121e7a279f","timestamp":"2026-04-23T19:13:27.103Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"bd25f7a2-9ecb-4f3f-9165-0b121e7a279f","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RD4eZaK4uHfny7CjWQ1wnP","name":"Agent","input":{"description":"User message structure deep dive","subagent_type":"Explore","prompt":"Deep dive into user message structure across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that processes all files and for every line where type==\"user\":\n1. Check if message.content is a string or an array\n2. If array, catalog every block type (text, tool_result, image, etc.) with examples of their structure (keys present, not full content)\n3. Check what top-level fields exist on user messages besides \"type\" and \"message\" (e.g. uuid, timestamp, parentUuid, sessionId, cwd, version, etc.)\n4. For tool_result blocks specifically: what fields do they have? Do they have nested content arrays?\n5. Show 2-3 representative examples of each user message variant (truncate long content to 100 chars)\n\nReport the full taxonomy with counts and structural examples.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"41ca15ed-1ed7-497a-b46d-c253e88999ce","timestamp":"2026-04-23T19:13:33.201Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"41ca15ed-1ed7-497a-b46d-c253e88999ce","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_015G6xevFdTkv3NkgKm85iWC","name":"Agent","input":{"description":"Assistant message structure deep dive","subagent_type":"Explore","prompt":"Deep dive into assistant message structure across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that processes all files and for every line where type==\"assistant\":\n1. Check if message.content is a string or an array\n2. If array, catalog every block type (text, tool_use, thinking, etc.) with their field structures\n3. For \"thinking\" blocks: what fields? Is it {type:\"thinking\", thinking:\"...\"} or something else?\n4. For \"tool_use\" blocks: what fields? (id, name, input, etc.)\n5. For \"text\" blocks: just {type:\"text\", text:\"...\"}? Any other fields?\n6. Any other block types we haven't seen?\n7. Check what top-level fields exist on assistant messages besides \"type\" and \"message\"\n8. Show 2-3 representative examples of each block type (truncate content to 100 chars)\n\nReport the full taxonomy with counts and structural examples.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"a7f92b9d-d195-408d-a168-7acac0d2e82c","timestamp":"2026-04-23T19:13:37.777Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"a7f92b9d-d195-408d-a168-7acac0d2e82c","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01R4mW5Vn1yFdijcDrLQQj6F","name":"Agent","input":{"description":"Special message types analysis","subagent_type":"Explore","prompt":"Analyze all NON-user, NON-assistant message types across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that for each line where type is NOT \"user\" or \"assistant\":\n1. Catalog every type value: attachment, file-history-snapshot, permission-mode, last-prompt, summary, system, etc.\n2. For each type, show the full JSON structure (keys only, not values) and 1-2 truncated examples\n3. For \"attachment\" type specifically: what are the different attachment.type sub-values? (deferred_tools_delta, mcp_instructions_delta, etc.)\n4. Look for any type that resembles a \"compact summary\" or \"context compaction\" marker\n5. Look for any \"system\" or \"system-reminder\" type messages\n6. Look for any \"summary\" type that Claude Code creates when compacting context\n7. Report which of these types carry useful conversational content vs pure metadata\n\nBe thorough — process every file, don't sample.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"d34b6725-2be3-4094-b71d-cbd7a93373e8","timestamp":"2026-04-23T19:13:44.006Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"d34b6725-2be3-4094-b71d-cbd7a93373e8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01HPxhhwPRcCWQzbrYLdDmoU","name":"Agent","input":{"description":"Bare directories investigation","subagent_type":"Explore","prompt":"In both session directories:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nSome UUIDs have bare directories (without .jsonl extension) alongside .jsonl files.\n\nInvestigate:\n1. List all bare directories (no .jsonl extension, not \"memory\")\n2. For each, check: does a matching .jsonl file also exist?\n3. What's inside these directories? List their contents recursively (ls -R)\n4. Are they related to resumed sessions, worktrees, or something else?\n5. Do they contain any files relevant to session content?\n\nReport findings — we need to know if these directories contain anything we should parse or if they're metadata only.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"336434bf-b7d1-4eee-a96e-2679093909d8","timestamp":"2026-04-23T19:13:48.379Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"336434bf-b7d1-4eee-a96e-2679093909d8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01VR69kdkK8yBRGtLSJHLTGr","name":"Agent","input":{"description":"Session size and length distribution","subagent_type":"Explore","prompt":"Analyze session size and conversation length across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that for each .jsonl file computes:\n1. File size in bytes\n2. Total line count\n3. Count of \"user\" type lines\n4. Count of \"assistant\" type lines  \n5. Count of other type lines\n6. First timestamp found (from any message with a timestamp field)\n7. Last timestamp found\n8. Total chars of extracted assistant text content (only type:\"text\" blocks)\n\nThen report:\n- Distribution summary: min, max, median, mean for each metric\n- The 5 smallest sessions (by assistant text chars) — these are our filter candidates\n- The 5 largest sessions\n- How many sessions would be filtered out by \"min 2 turn pairs AND min 200 chars assistant text\"","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"cc566aa2-0bf2-452f-966e-07db0d4b27c3","timestamp":"2026-04-23T19:13:54.727Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"cc566aa2-0bf2-452f-966e-07db0d4b27c3","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01676oJccvGAMBe4NggEfkzU","name":"Agent","input":{"description":"Edge case sessions analysis","subagent_type":"Explore","prompt":"Find and analyze edge case sessions across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script to identify:\n1. Sessions with 0 or 1 user messages — what do they contain?\n2. Sessions where ALL user messages start with \"/\" (config-only sessions)\n3. Sessions with no assistant text blocks at all\n4. Sessions that appear to be \"resumed\" — look for multiple permission-mode entries or gaps in timestamps\n5. Sessions where user content is ONLY tool_result blocks (no text) — are there follow-up turns?\n6. Any sessions with malformed JSON lines (parse errors)\n7. Sessions that contain what looks like a compaction/summary event\n\nFor each edge case found, show the session UUID and a brief description of what makes it unusual. This helps us define our filtering heuristics.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"5948acb9-2221-404d-a227-6e5258a0cf39","timestamp":"2026-04-23T19:14:00.014Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"5948acb9-2221-404d-a227-6e5258a0cf39","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_015joRcwrnRtWsGyKYRgSRNS","name":"Agent","input":{"description":"Tool usage metadata extraction","subagent_type":"Explore","prompt":"Analyze tool_use blocks in assistant messages across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that:\n1. For every assistant message, extract all tool_use block \"name\" fields\n2. Build a frequency table of tool names used across all sessions\n3. For the top 20 tools, show example tool_use block structure (keys only, truncated)\n4. Check: are tool names always in tool_use.name? Any variants?\n5. Count how many tool_use blocks appear per assistant message on average\n6. Check if tool_use blocks ever contain nested content we'd want to preserve\n\nThis data informs our metadata extraction — we plan to include tool names in chunk titles for BM25 searchability. We need the exact field paths and tool name formats.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"2b265eb1-f7e8-4429-9ded-dee9c696431d","timestamp":"2026-04-23T19:14:04.858Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"2b265eb1-f7e8-4429-9ded-dee9c696431d","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01JRc4pV87sAjm4Q4eNEDWAw","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AdEQ1jLZFyDyiyc6W63nDs","name":"Agent","input":{"description":"Slash commands and noise patterns","subagent_type":"Explore","prompt":"Analyze user message content patterns across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that for every user message with text content:\n1. Identify all messages that start with \"/\" — catalog every slash command found (e.g. /config, /compact, /help, /clear, etc.) with counts\n2. Identify very short messages (< 20 chars) — what do they say? Are they meaningful?\n3. Identify messages that are ONLY tool_result blocks with no human text — these are automatic tool result returns, not human input\n4. Check: do user messages ever contain \"system-reminder\" text? Or is that only in the content blocks?\n5. Look for patterns that indicate \"noise\" vs \"signal\" in human messages — what should we skip vs keep?\n6. Are there user messages with type:\"text\" blocks that contain system-injected content (like system-reminder tags)?\n\nThis informs our per-message filtering heuristics. Report all patterns found with counts and examples.","run_in_background":true},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":3657,"cache_read_input_tokens":93843,"output_tokens":3582,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3657,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEavXgCFoCoi7sEehMR","type":"assistant","uuid":"2da86ebd-6f0e-4a11-9b3b-249d261bdf8d","timestamp":"2026-04-23T19:14:11.636Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"2da86ebd-6f0e-4a11-9b3b-249d261bdf8d","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01Jc216enu4HTqt8eFqJKK2L","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Session types catalog (capy)\",\"prompt\":\"Analyze ALL .jsonl session files in ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n\\nFor each file, parse every line as JSON and collect:\\n1. Every unique `type` field value\\n2. For each type, count how many times it appears across all files\\n3. For types \\\"user\\\" and \\\"assistant\\\", also collect every unique content block `type` (e.g. \\\"text\\\", \\\"tool_use\\\", \\\"tool_result\\\", \\\"thinking\\\", \\\"image\\\", etc.)\\n\\nUse a Python script via Bash to process all files at once. Report the complete taxonomy of types and content block types with counts. Be thorough — don't sample, process every file.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":14},"type":"attachment","uuid":"c1641f50-4959-4a0c-87dc-77b18b0e8536","timestamp":"2026-04-23T19:14:11.695Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"3867f770-a9d6-4571-a189-fb06a51d926c","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Jc216enu4HTqt8eFqJKK2L","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: a48caad27c387cd16 (internal ID - do not mention to user. Use SendMessage with to: 'a48caad27c387cd16' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a48caad27c387cd16.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"c0f5db90-fcf2-407e-9b32-456ffea1ea76","timestamp":"2026-04-23T19:14:11.699Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"a48caad27c387cd16","description":"Session types catalog (capy)","prompt":"Analyze ALL .jsonl session files in ~/.claude/projects/-home-sergio-Projects-personal-capy/\n\nFor each file, parse every line as JSON and collect:\n1. Every unique `type` field value\n2. For each type, count how many times it appears across all files\n3. For types \"user\" and \"assistant\", also collect every unique content block `type` (e.g. \"text\", \"tool_use\", \"tool_result\", \"thinking\", \"image\", etc.)\n\nUse a Python script via Bash to process all files at once. Report the complete taxonomy of types and content block types with counts. Be thorough — don't sample, process every file.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a48caad27c387cd16.output","canReadOutputFile":true},"sourceToolAssistantUUID":"3867f770-a9d6-4571-a189-fb06a51d926c","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"c0f5db90-fcf2-407e-9b32-456ffea1ea76","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01JcfzaM6xRJ8ruTbLiBGnu5","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Session types catalog (toolbox)\",\"prompt\":\"Analyze ALL .jsonl session files in ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nFor each file, parse every line as JSON and collect:\\n1. Every unique `type` field value\\n2. For each type, count how many times it appears across all files\\n3. For types \\\"user\\\" and \\\"assistant\\\", also collect every unique content block `type` (e.g. \\\"text\\\", \\\"tool_use\\\", \\\"tool_result\\\", \\\"thinking\\\", \\\"image\\\", etc.)\\n\\nUse a Python script via Bash to process all files at once. Report the complete taxonomy of types and content block types with counts. Be thorough — don't sample, process every file.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":21},"type":"attachment","uuid":"94d1c553-879e-4ed9-a765-fd0504df1d62","timestamp":"2026-04-23T19:14:11.702Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"bd25f7a2-9ecb-4f3f-9165-0b121e7a279f","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JcfzaM6xRJ8ruTbLiBGnu5","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: ad2bce71a5258fd65 (internal ID - do not mention to user. Use SendMessage with to: 'ad2bce71a5258fd65' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad2bce71a5258fd65.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"43e039bf-ba99-4294-bf79-21774d9a5d3c","timestamp":"2026-04-23T19:14:11.704Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"ad2bce71a5258fd65","description":"Session types catalog (toolbox)","prompt":"Analyze ALL .jsonl session files in ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nFor each file, parse every line as JSON and collect:\n1. Every unique `type` field value\n2. For each type, count how many times it appears across all files\n3. For types \"user\" and \"assistant\", also collect every unique content block `type` (e.g. \"text\", \"tool_use\", \"tool_result\", \"thinking\", \"image\", etc.)\n\nUse a Python script via Bash to process all files at once. Report the complete taxonomy of types and content block types with counts. Be thorough — don't sample, process every file.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad2bce71a5258fd65.output","canReadOutputFile":true},"sourceToolAssistantUUID":"bd25f7a2-9ecb-4f3f-9165-0b121e7a279f","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"43e039bf-ba99-4294-bf79-21774d9a5d3c","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01RD4eZaK4uHfny7CjWQ1wnP","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"User message structure deep dive\",\"prompt\":\"Deep dive into user message structure across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script that processes all files and for every line where type==\\\"user\\\":\\n1. Check if message.content is a string or an array\\n2. If array, catalog every block type (text, tool_result, image, etc.) with examples of their structure (keys present, not full content)\\n3. Check what top-level fields exist on user messages besides \\\"type\\\" and \\\"message\\\" (e.g. uuid, timestamp, parentUuid, sessionId, cwd, version, etc.)\\n4. For tool_result blocks specifically: what fields do they have? Do they have nested content arrays?\\n5. Show 2-3 representative examples of each user message variant (truncate long content to 100 chars)\\n\\nReport the full taxonomy with counts and structural examples.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":27},"type":"attachment","uuid":"1bd6fd4c-6ac8-4b25-b4bc-ed889919a9bf","timestamp":"2026-04-23T19:14:11.708Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"41ca15ed-1ed7-497a-b46d-c253e88999ce","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RD4eZaK4uHfny7CjWQ1wnP","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: ad24cff58eef19977 (internal ID - do not mention to user. Use SendMessage with to: 'ad24cff58eef19977' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad24cff58eef19977.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"833ce220-1189-43f0-b152-76bbb4f1a12e","timestamp":"2026-04-23T19:14:11.710Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"ad24cff58eef19977","description":"User message structure deep dive","prompt":"Deep dive into user message structure across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that processes all files and for every line where type==\"user\":\n1. Check if message.content is a string or an array\n2. If array, catalog every block type (text, tool_result, image, etc.) with examples of their structure (keys present, not full content)\n3. Check what top-level fields exist on user messages besides \"type\" and \"message\" (e.g. uuid, timestamp, parentUuid, sessionId, cwd, version, etc.)\n4. For tool_result blocks specifically: what fields do they have? Do they have nested content arrays?\n5. Show 2-3 representative examples of each user message variant (truncate long content to 100 chars)\n\nReport the full taxonomy with counts and structural examples.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad24cff58eef19977.output","canReadOutputFile":true},"sourceToolAssistantUUID":"41ca15ed-1ed7-497a-b46d-c253e88999ce","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"833ce220-1189-43f0-b152-76bbb4f1a12e","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_015G6xevFdTkv3NkgKm85iWC","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Assistant message structure deep dive\",\"prompt\":\"Deep dive into assistant message structure across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script that processes all files and for every line where type==\\\"assistant\\\":\\n1. Check if message.content is a string or an array\\n2. If array, catalog every block type (text, tool_use, thinking, etc.) with their field structures\\n3. For \\\"thinking\\\" blocks: what fields? Is it {type:\\\"thinking\\\", thinking:\\\"...\\\"} or something else?\\n4. For \\\"tool_use\\\" blocks: what fields? (id, name, input, etc.)\\n5. For \\\"text\\\" blocks: just {type:\\\"text\\\", text:\\\"...\\\"}? Any other fields?\\n6. Any other block types we haven't seen?\\n7. Check what top-level fields exist on assistant messages besides \\\"type\\\" and \\\"message\\\"\\n8. Show 2-3 representative examples of each block type (truncate content to 100 chars)\\n\\nReport the full taxonomy with counts and structural examples.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":24},"type":"attachment","uuid":"0baec1f9-f846-42ac-9dff-0ca6ea6547be","timestamp":"2026-04-23T19:14:11.705Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"a7f92b9d-d195-408d-a168-7acac0d2e82c","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015G6xevFdTkv3NkgKm85iWC","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: a616b05a42c414f0c (internal ID - do not mention to user. Use SendMessage with to: 'a616b05a42c414f0c' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a616b05a42c414f0c.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"ce556d61-8f08-4573-a517-f75eeb6dcf78","timestamp":"2026-04-23T19:14:11.707Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"a616b05a42c414f0c","description":"Assistant message structure deep dive","prompt":"Deep dive into assistant message structure across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that processes all files and for every line where type==\"assistant\":\n1. Check if message.content is a string or an array\n2. If array, catalog every block type (text, tool_use, thinking, etc.) with their field structures\n3. For \"thinking\" blocks: what fields? Is it {type:\"thinking\", thinking:\"...\"} or something else?\n4. For \"tool_use\" blocks: what fields? (id, name, input, etc.)\n5. For \"text\" blocks: just {type:\"text\", text:\"...\"}? Any other fields?\n6. Any other block types we haven't seen?\n7. Check what top-level fields exist on assistant messages besides \"type\" and \"message\"\n8. Show 2-3 representative examples of each block type (truncate content to 100 chars)\n\nReport the full taxonomy with counts and structural examples.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a616b05a42c414f0c.output","canReadOutputFile":true},"sourceToolAssistantUUID":"a7f92b9d-d195-408d-a168-7acac0d2e82c","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"ce556d61-8f08-4573-a517-f75eeb6dcf78","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01HPxhhwPRcCWQzbrYLdDmoU","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Bare directories investigation\",\"prompt\":\"In both session directories:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nSome UUIDs have bare directories (without .jsonl extension) alongside .jsonl files.\\n\\nInvestigate:\\n1. List all bare directories (no .jsonl extension, not \\\"memory\\\")\\n2. For each, check: does a matching .jsonl file also exist?\\n3. What's inside these directories? List their contents recursively (ls -R)\\n4. Are they related to resumed sessions, worktrees, or something else?\\n5. Do they contain any files relevant to session content?\\n\\nReport findings — we need to know if these directories contain anything we should parse or if they're metadata only.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":33},"type":"attachment","uuid":"c0f10aca-6172-4332-bc65-ab47e1da8944","timestamp":"2026-04-23T19:14:11.714Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"336434bf-b7d1-4eee-a96e-2679093909d8","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HPxhhwPRcCWQzbrYLdDmoU","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: ad4f2f55bcf82d098 (internal ID - do not mention to user. Use SendMessage with to: 'ad4f2f55bcf82d098' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad4f2f55bcf82d098.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"e9b7b957-9c8c-43e7-a5e3-b8e313523b03","timestamp":"2026-04-23T19:14:11.716Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"ad4f2f55bcf82d098","description":"Bare directories investigation","prompt":"In both session directories:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nSome UUIDs have bare directories (without .jsonl extension) alongside .jsonl files.\n\nInvestigate:\n1. List all bare directories (no .jsonl extension, not \"memory\")\n2. For each, check: does a matching .jsonl file also exist?\n3. What's inside these directories? List their contents recursively (ls -R)\n4. Are they related to resumed sessions, worktrees, or something else?\n5. Do they contain any files relevant to session content?\n\nReport findings — we need to know if these directories contain anything we should parse or if they're metadata only.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad4f2f55bcf82d098.output","canReadOutputFile":true},"sourceToolAssistantUUID":"336434bf-b7d1-4eee-a96e-2679093909d8","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"e9b7b957-9c8c-43e7-a5e3-b8e313523b03","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01R4mW5Vn1yFdijcDrLQQj6F","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Special message types analysis\",\"prompt\":\"Analyze all NON-user, NON-assistant message types across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script that for each line where type is NOT \\\"user\\\" or \\\"assistant\\\":\\n1. Catalog every type value: attachment, file-history-snapshot, permission-mode, last-prompt, summary, system, etc.\\n2. For each type, show the full JSON structure (keys only, not values) and 1-2 truncated examples\\n3. For \\\"attachment\\\" type specifically: what are the different attachment.type sub-values? (deferred_tools_delta, mcp_instructions_delta, etc.)\\n4. Look for any type that resembles a \\\"compact summary\\\" or \\\"context compaction\\\" marker\\n5. Look for any \\\"system\\\" or \\\"system-reminder\\\" type messages\\n6. Look for any \\\"summary\\\" type that Claude Code creates when compacting context\\n7. Report which of these types carry useful conversational content vs pure metadata\\n\\nBe thorough — process every file, don't sample.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":30},"type":"attachment","uuid":"59ffbd6f-a280-4b42-a901-c014eb7befa8","timestamp":"2026-04-23T19:14:11.711Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"d34b6725-2be3-4094-b71d-cbd7a93373e8","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01R4mW5Vn1yFdijcDrLQQj6F","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: acb8ca54b83b68f7d (internal ID - do not mention to user. Use SendMessage with to: 'acb8ca54b83b68f7d' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/acb8ca54b83b68f7d.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"59f7830a-6f8a-4c77-8bae-d084723e0e5d","timestamp":"2026-04-23T19:14:11.713Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"acb8ca54b83b68f7d","description":"Special message types analysis","prompt":"Analyze all NON-user, NON-assistant message types across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that for each line where type is NOT \"user\" or \"assistant\":\n1. Catalog every type value: attachment, file-history-snapshot, permission-mode, last-prompt, summary, system, etc.\n2. For each type, show the full JSON structure (keys only, not values) and 1-2 truncated examples\n3. For \"attachment\" type specifically: what are the different attachment.type sub-values? (deferred_tools_delta, mcp_instructions_delta, etc.)\n4. Look for any type that resembles a \"compact summary\" or \"context compaction\" marker\n5. Look for any \"system\" or \"system-reminder\" type messages\n6. Look for any \"summary\" type that Claude Code creates when compacting context\n7. Report which of these types carry useful conversational content vs pure metadata\n\nBe thorough — process every file, don't sample.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/acb8ca54b83b68f7d.output","canReadOutputFile":true},"sourceToolAssistantUUID":"d34b6725-2be3-4094-b71d-cbd7a93373e8","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"59f7830a-6f8a-4c77-8bae-d084723e0e5d","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01676oJccvGAMBe4NggEfkzU","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Edge case sessions analysis\",\"prompt\":\"Find and analyze edge case sessions across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script to identify:\\n1. Sessions with 0 or 1 user messages — what do they contain?\\n2. Sessions where ALL user messages start with \\\"/\\\" (config-only sessions)\\n3. Sessions with no assistant text blocks at all\\n4. Sessions that appear to be \\\"resumed\\\" — look for multiple permission-mode entries or gaps in timestamps\\n5. Sessions where user content is ONLY tool_result blocks (no text) — are there follow-up turns?\\n6. Any sessions with malformed JSON lines (parse errors)\\n7. Sessions that contain what looks like a compaction/summary event\\n\\nFor each edge case found, show the session UUID and a brief description of what makes it unusual. This helps us define our filtering heuristics.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":36},"type":"attachment","uuid":"8b4560e0-6c21-4e75-b21c-b8019bf46599","timestamp":"2026-04-23T19:14:11.717Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"5948acb9-2221-404d-a227-6e5258a0cf39","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01676oJccvGAMBe4NggEfkzU","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: ab34b1b13cd33756b (internal ID - do not mention to user. Use SendMessage with to: 'ab34b1b13cd33756b' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ab34b1b13cd33756b.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"3095b7d2-5906-4590-8dba-00333ef66cdd","timestamp":"2026-04-23T19:14:11.719Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"ab34b1b13cd33756b","description":"Edge case sessions analysis","prompt":"Find and analyze edge case sessions across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script to identify:\n1. Sessions with 0 or 1 user messages — what do they contain?\n2. Sessions where ALL user messages start with \"/\" (config-only sessions)\n3. Sessions with no assistant text blocks at all\n4. Sessions that appear to be \"resumed\" — look for multiple permission-mode entries or gaps in timestamps\n5. Sessions where user content is ONLY tool_result blocks (no text) — are there follow-up turns?\n6. Any sessions with malformed JSON lines (parse errors)\n7. Sessions that contain what looks like a compaction/summary event\n\nFor each edge case found, show the session UUID and a brief description of what makes it unusual. This helps us define our filtering heuristics.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ab34b1b13cd33756b.output","canReadOutputFile":true},"sourceToolAssistantUUID":"5948acb9-2221-404d-a227-6e5258a0cf39","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"3095b7d2-5906-4590-8dba-00333ef66cdd","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_015joRcwrnRtWsGyKYRgSRNS","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Tool usage metadata extraction\",\"prompt\":\"Analyze tool_use blocks in assistant messages across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script that:\\n1. For every assistant message, extract all tool_use block \\\"name\\\" fields\\n2. Build a frequency table of tool names used across all sessions\\n3. For the top 20 tools, show example tool_use block structure (keys only, truncated)\\n4. Check: are tool names always in tool_use.name? Any variants?\\n5. Count how many tool_use blocks appear per assistant message on average\\n6. Check if tool_use blocks ever contain nested content we'd want to preserve\\n\\nThis data informs our metadata extraction — we plan to include tool names in chunk titles for BM25 searchability. We need the exact field paths and tool name formats.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":39},"type":"attachment","uuid":"d319655d-e380-4747-96ef-41742d6dcf3f","timestamp":"2026-04-23T19:14:11.720Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"2b265eb1-f7e8-4429-9ded-dee9c696431d","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015joRcwrnRtWsGyKYRgSRNS","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: a5c523c552380c08b (internal ID - do not mention to user. Use SendMessage with to: 'a5c523c552380c08b' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a5c523c552380c08b.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"8177730f-3158-4e8d-8d87-cfd217e8ff28","timestamp":"2026-04-23T19:14:11.722Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"a5c523c552380c08b","description":"Tool usage metadata extraction","prompt":"Analyze tool_use blocks in assistant messages across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that:\n1. For every assistant message, extract all tool_use block \"name\" fields\n2. Build a frequency table of tool names used across all sessions\n3. For the top 20 tools, show example tool_use block structure (keys only, truncated)\n4. Check: are tool names always in tool_use.name? Any variants?\n5. Count how many tool_use blocks appear per assistant message on average\n6. Check if tool_use blocks ever contain nested content we'd want to preserve\n\nThis data informs our metadata extraction — we plan to include tool names in chunk titles for BM25 searchability. We need the exact field paths and tool name formats.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a5c523c552380c08b.output","canReadOutputFile":true},"sourceToolAssistantUUID":"2b265eb1-f7e8-4429-9ded-dee9c696431d","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"8177730f-3158-4e8d-8d87-cfd217e8ff28","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01VR69kdkK8yBRGtLSJHLTGr","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Session size and length distribution\",\"prompt\":\"Analyze session size and conversation length across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script that for each .jsonl file computes:\\n1. File size in bytes\\n2. Total line count\\n3. Count of \\\"user\\\" type lines\\n4. Count of \\\"assistant\\\" type lines  \\n5. Count of other type lines\\n6. First timestamp found (from any message with a timestamp field)\\n7. Last timestamp found\\n8. Total chars of extracted assistant text content (only type:\\\"text\\\" blocks)\\n\\nThen report:\\n- Distribution summary: min, max, median, mean for each metric\\n- The 5 smallest sessions (by assistant text chars) — these are our filter candidates\\n- The 5 largest sessions\\n- How many sessions would be filtered out by \\\"min 2 turn pairs AND min 200 chars assistant text\\\"\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":41},"type":"attachment","uuid":"062d5498-199c-4b3e-83cc-dae206784f66","timestamp":"2026-04-23T19:14:11.722Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"cc566aa2-0bf2-452f-966e-07db0d4b27c3","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VR69kdkK8yBRGtLSJHLTGr","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: a7a78d8cd05d0258e (internal ID - do not mention to user. Use SendMessage with to: 'a7a78d8cd05d0258e' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a7a78d8cd05d0258e.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"4f02f13e-7860-4b5c-beeb-1c56c5365121","timestamp":"2026-04-23T19:14:11.725Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"a7a78d8cd05d0258e","description":"Session size and length distribution","prompt":"Analyze session size and conversation length across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that for each .jsonl file computes:\n1. File size in bytes\n2. Total line count\n3. Count of \"user\" type lines\n4. Count of \"assistant\" type lines  \n5. Count of other type lines\n6. First timestamp found (from any message with a timestamp field)\n7. Last timestamp found\n8. Total chars of extracted assistant text content (only type:\"text\" blocks)\n\nThen report:\n- Distribution summary: min, max, median, mean for each metric\n- The 5 smallest sessions (by assistant text chars) — these are our filter candidates\n- The 5 largest sessions\n- How many sessions would be filtered out by \"min 2 turn pairs AND min 200 chars assistant text\"<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a7a78d8cd05d0258e.output","canReadOutputFile":true},"sourceToolAssistantUUID":"cc566aa2-0bf2-452f-966e-07db0d4b27c3","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"4f02f13e-7860-4b5c-beeb-1c56c5365121","isSidechain":false,"attachment":{"type":"hook_success","hookName":"PreToolUse:Agent","toolUseID":"toolu_01AdEQ1jLZFyDyiyc6W63nDs","hookEvent":"PreToolUse","content":"","stdout":"{\"hookSpecificOutput\":{\"hookEventName\":\"PreToolUse\",\"permissionDecision\":\"allow\",\"permissionDecisionReason\":\"Routed to capy sandbox\",\"updatedInput\":{\"description\":\"Slash commands and noise patterns\",\"prompt\":\"Analyze user message content patterns across ALL .jsonl files in both:\\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\\n\\nWrite a Python script that for every user message with text content:\\n1. Identify all messages that start with \\\"/\\\" — catalog every slash command found (e.g. /config, /compact, /help, /clear, etc.) with counts\\n2. Identify very short messages (\\u003c 20 chars) — what do they say? Are they meaningful?\\n3. Identify messages that are ONLY tool_result blocks with no human text — these are automatic tool result returns, not human input\\n4. Check: do user messages ever contain \\\"system-reminder\\\" text? Or is that only in the content blocks?\\n5. Look for patterns that indicate \\\"noise\\\" vs \\\"signal\\\" in human messages — what should we skip vs keep?\\n6. Are there user messages with type:\\\"text\\\" blocks that contain system-injected content (like system-reminder tags)?\\n\\nThis informs our per-message filtering heuristics. Report all patterns found with counts and examples.\\u003ccontext_window_protection\\u003e\\n  \\u003cpriority_instructions\\u003e\\n    Raw tool output floods your context window. You MUST use capy\\n    MCP tools to keep raw data in the sandbox.\\n  \\u003c/priority_instructions\\u003e\\n\\n  \\u003ctool_selection_hierarchy\\u003e\\n    1. GATHER: capy_batch_execute(commands, queries)\\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\\n       - ONE call replaces many individual steps.\\n    2. FOLLOW-UP: capy_search(queries: [\\\"q1\\\", \\\"q2\\\", ...])\\n       - Use for all follow-up questions. ONE call, many queries.\\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\\n       - Use for API calls, log analysis, and data processing.\\n  \\u003c/tool_selection_hierarchy\\u003e\\n\\n  \\u003cforbidden_actions\\u003e\\n    - DO NOT use Bash for commands producing \\u003e20 lines of output.\\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\\n  \\u003c/forbidden_actions\\u003e\\n\\n  \\u003coutput_constraints\\u003e\\n    \\u003cword_limit\\u003eKeep your final response under 500 words.\\u003c/word_limit\\u003e\\n    \\u003cartifact_policy\\u003e\\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\\n      Return only: file path + 1-line description.\\n    \\u003c/artifact_policy\\u003e\\n    \\u003cresponse_format\\u003e\\n      Your response must be a concise summary:\\n      - Actions taken (2-3 bullets)\\n      - File paths created/modified\\n      - Knowledge base source labels (so parent can search)\\n      - Key findings\\n    \\u003c/response_format\\u003e\\n  \\u003c/output_constraints\\u003e\\n\\n  \\u003ccapy_commands\\u003e\\n    When the user says \\\"capy stats\\\" or asks about context savings:\\n    → Call the capy_stats MCP tool and display the full output verbatim.\\n\\n    When the user says \\\"capy doctor\\\" or asks to diagnose capy:\\n    → Call the capy_doctor MCP tool and display results as a checklist.\\n  \\u003c/capy_commands\\u003e\\n\\u003c/context_window_protection\\u003e\",\"run_in_background\":true,\"subagent_type\":\"Explore\"}}}","stderr":"","exitCode":0,"command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse","durationMs":44},"type":"attachment","uuid":"90aed2d4-3aab-454d-8ba7-300bcd3e1311","timestamp":"2026-04-23T19:14:11.726Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"2da86ebd-6f0e-4a11-9b3b-249d261bdf8d","isSidechain":false,"promptId":"2a48c266-8b38-4ea7-a09f-6457057766c5","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AdEQ1jLZFyDyiyc6W63nDs","type":"tool_result","content":[{"type":"text","text":"Async agent launched successfully.\nagentId: ae5e6c1956e56c56e (internal ID - do not mention to user. Use SendMessage with to: 'ae5e6c1956e56c56e' to continue this agent.)\nThe agent is working in the background. You will be notified automatically when it completes.\nDo not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.\noutput_file: /tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ae5e6c1956e56c56e.output\nDo NOT Read or Bash tail this file — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification."}]}]},"uuid":"142fe541-703b-454c-a02f-85715d6b77f7","timestamp":"2026-04-23T19:14:11.728Z","toolUseResult":{"isAsync":true,"status":"async_launched","agentId":"ae5e6c1956e56c56e","description":"Slash commands and noise patterns","prompt":"Analyze user message content patterns across ALL .jsonl files in both:\n- ~/.claude/projects/-home-sergio-Projects-personal-capy/\n- ~/.claude/projects/-home-sergio-Projects-personal-claude-toolbox/\n\nWrite a Python script that for every user message with text content:\n1. Identify all messages that start with \"/\" — catalog every slash command found (e.g. /config, /compact, /help, /clear, etc.) with counts\n2. Identify very short messages (< 20 chars) — what do they say? Are they meaningful?\n3. Identify messages that are ONLY tool_result blocks with no human text — these are automatic tool result returns, not human input\n4. Check: do user messages ever contain \"system-reminder\" text? Or is that only in the content blocks?\n5. Look for patterns that indicate \"noise\" vs \"signal\" in human messages — what should we skip vs keep?\n6. Are there user messages with type:\"text\" blocks that contain system-injected content (like system-reminder tags)?\n\nThis informs our per-message filtering heuristics. Report all patterns found with counts and examples.<context_window_protection>\n  <priority_instructions>\n    Raw tool output floods your context window. You MUST use capy\n    MCP tools to keep raw data in the sandbox.\n  </priority_instructions>\n\n  <tool_selection_hierarchy>\n    1. GATHER: capy_batch_execute(commands, queries)\n       - Primary tool for research. Runs all commands, auto-indexes, and searches.\n       - ONE call replaces many individual steps.\n    2. FOLLOW-UP: capy_search(queries: [\"q1\", \"q2\", ...])\n       - Use for all follow-up questions. ONE call, many queries.\n    3. PROCESSING: capy_execute(language, code) | capy_execute_file(path, language, code)\n       - Use for API calls, log analysis, and data processing.\n  </tool_selection_hierarchy>\n\n  <forbidden_actions>\n    - DO NOT use Bash for commands producing >20 lines of output.\n    - DO NOT use Read for analysis (use execute_file). Read IS correct for files you intend to Edit.\n    - DO NOT use WebFetch (use capy_fetch_and_index instead).\n    - Bash is ONLY for git/mkdir/rm/mv/navigation.\n  </forbidden_actions>\n\n  <output_constraints>\n    <word_limit>Keep your final response under 500 words.</word_limit>\n    <artifact_policy>\n      Write artifacts (code, configs, PRDs) to FILES. NEVER return them as inline text.\n      Return only: file path + 1-line description.\n    </artifact_policy>\n    <response_format>\n      Your response must be a concise summary:\n      - Actions taken (2-3 bullets)\n      - File paths created/modified\n      - Knowledge base source labels (so parent can search)\n      - Key findings\n    </response_format>\n  </output_constraints>\n\n  <capy_commands>\n    When the user says \"capy stats\" or asks about context savings:\n    → Call the capy_stats MCP tool and display the full output verbatim.\n\n    When the user says \"capy doctor\" or asks to diagnose capy:\n    → Call the capy_doctor MCP tool and display results as a checklist.\n  </capy_commands>\n</context_window_protection>","outputFile":"/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ae5e6c1956e56c56e.output","canReadOutputFile":true},"sourceToolAssistantUUID":"2da86ebd-6f0e-4a11-9b3b-249d261bdf8d","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"142fe541-703b-454c-a02f-85715d6b77f7","isSidechain":false,"attachment":{"type":"task_reminder","content":[],"itemCount":0},"type":"attachment","uuid":"3890992c-b0da-4f55-b1ce-5f08dc541fbc","timestamp":"2026-04-23T19:14:11.774Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"last-prompt","lastPrompt":"Looks good, but have you thorougly explored the jsonl files and are confident what we keep vs what we drop? You can use @~/.claude/projects/-home-sergio-Projects-personal-capy and @~/.claude/projects/…","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"permission-mode","permissionMode":"default","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"3890992c-b0da-4f55-b1ce-5f08dc541fbc","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01MfdRBkkDN5xjQaFThEwuYE","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"EtUCClkIDRgCKkCYwX8GP+c3n9JFJaKJ5LdV1H2iqN1/FJ2WICBCslwcyag3vSSIUbCWLRKHE9k38lDFkCH5IEfFDkVvdEsYNaS/Mg9jbGF1ZGUtb3B1cy00LTY4ABIMyXMludqYyXxq1XlXGgwhUrTdYu1Mm9ib5f8iMKhnokf0Dd49fKxL/UkaSyk8kiK7X/6NNLKzbCHT3gMV61nLkmBOj+jx/laKlQDhWCqpAVc7sIGqid3H2OZa3/EyMzCU749jyWWYRK+yUyeh5hkjY+d0hqbjxQUhT9BvBcXtOlihhBzvCxJAMkJ4ocClQKgA0S4bJ6zKus/Q8poiaVhplvZ7OCGrB8Twj1LgOH4htxZ6rVKFvCq8e3mqoqA1J158IRLrLkLPJbbnCD98Bkkh6XHVamsECQJ3uZ7rBV8PXmtGBLHpyJuEIaZfbtnLrz9CPfLOi7dN/BQYAQ=="}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":91642,"cache_read_input_tokens":12127,"output_tokens":236,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":91642,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEfZHd9ygHmSvv4yMLs","type":"assistant","uuid":"6ab6c757-ea8f-4df8-881b-0f89cb15c676","timestamp":"2026-04-23T19:14:16.086Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"6ab6c757-ea8f-4df8-881b-0f89cb15c676","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01MfdRBkkDN5xjQaFThEwuYE","type":"message","role":"assistant","content":[{"type":"text","text":"All 10 agents launched. They're analyzing:\n\n1. **Types catalog** — every message type across capy sessions\n2. **Types catalog** — same for claude-toolbox sessions\n3. **User message structure** — content formats, block types, field structures\n4. **Assistant message structure** — text, thinking, tool_use block details\n5. **Special message types** — attachments, snapshots, compact markers, system messages\n6. **Bare directories** — what the non-JSONL entries are\n7. **Size/length distribution** — session metrics, filter threshold impact\n8. **Edge cases** — short sessions, config-only, resumed, malformed\n9. **Tool usage metadata** — tool name formats and frequencies\n10. **Slash commands & noise** — user message patterns to filter\n\nI'll synthesize findings as they come back."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":91642,"cache_read_input_tokens":12127,"output_tokens":236,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":91642,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEfZHd9ygHmSvv4yMLs","type":"assistant","uuid":"c7dd5002-f052-4ea8-91b5-3e35a4fe0f25","timestamp":"2026-04-23T19:14:20.309Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"c7dd5002-f052-4ea8-91b5-3e35a4fe0f25","isSidechain":false,"type":"system","subtype":"turn_duration","durationMs":71400,"messageCount":210,"timestamp":"2026-04-23T19:14:20.352Z","uuid":"f0b84ae1-d337-4686-b01b-a3dfc9e7a443","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:14:28.711Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>ad2bce71a5258fd65</task-id>\n<tool-use-id>toolu_01JcfzaM6xRJ8ruTbLiBGnu5</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad2bce71a5258fd65.output</output-file>\n<status>completed</status>\n<summary>Agent \"Session types catalog (toolbox)\" completed</summary>\n<result>Here is the complete taxonomy across all 64 JSONL files (6,475 lines, 0 parse errors):\n\n**Top-level `type` field counts:**\n\n| type | count |\n|---|---|\n| assistant | 2,838 |\n| user | 2,024 |\n| file-history-snapshot | 436 |\n| attachment | 335 |\n| permission-mode | 317 |\n| last-prompt | 223 |\n| system | 162 |\n| progress | 108 |\n| queue-operation | 20 |\n| custom-title | 6 |\n| agent-name | 6 |\n\n**`user` message content block types:**\n\n| content type | count |\n|---|---|\n| tool_result | 1,569 |\n| text (string, not block) | 407 |\n| text (block object) | 48 |\n\n**`assistant` message content block types:**\n\n| content type | count |\n|---|---|\n| tool_use | 1,570 |\n| text | 674 |\n| thinking | 595 |\n\nKey observations:\n- `thinking` blocks appear 595 times in assistant messages, indicating extended thinking is used heavily in this project.\n- `tool_use` / `tool_result` are nearly perfectly paired (1,570 vs 1,569), as expected.\n- User `text` content splits between raw strings (407) and structured text blocks (48).\n- Claude's internal record-keeping types (file-history-snapshot, attachment, permission-mode, last-prompt) account for over 1,300 lines.</result>\n<usage><total_tokens>13937</total_tokens><tool_uses>2</tool_uses><duration_ms>17008</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:14:28.746Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"f0b84ae1-d337-4686-b01b-a3dfc9e7a443","isSidechain":false,"promptId":"3ed2d9b6-3272-4ee2-b3c2-dba8fc453678","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>ad2bce71a5258fd65</task-id>\n<tool-use-id>toolu_01JcfzaM6xRJ8ruTbLiBGnu5</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad2bce71a5258fd65.output</output-file>\n<status>completed</status>\n<summary>Agent \"Session types catalog (toolbox)\" completed</summary>\n<result>Here is the complete taxonomy across all 64 JSONL files (6,475 lines, 0 parse errors):\n\n**Top-level `type` field counts:**\n\n| type | count |\n|---|---|\n| assistant | 2,838 |\n| user | 2,024 |\n| file-history-snapshot | 436 |\n| attachment | 335 |\n| permission-mode | 317 |\n| last-prompt | 223 |\n| system | 162 |\n| progress | 108 |\n| queue-operation | 20 |\n| custom-title | 6 |\n| agent-name | 6 |\n\n**`user` message content block types:**\n\n| content type | count |\n|---|---|\n| tool_result | 1,569 |\n| text (string, not block) | 407 |\n| text (block object) | 48 |\n\n**`assistant` message content block types:**\n\n| content type | count |\n|---|---|\n| tool_use | 1,570 |\n| text | 674 |\n| thinking | 595 |\n\nKey observations:\n- `thinking` blocks appear 595 times in assistant messages, indicating extended thinking is used heavily in this project.\n- `tool_use` / `tool_result` are nearly perfectly paired (1,570 vs 1,569), as expected.\n- User `text` content splits between raw strings (407) and structured text blocks (48).\n- Claude's internal record-keeping types (file-history-snapshot, attachment, permission-mode, last-prompt) account for over 1,300 lines.</result>\n<usage><total_tokens>13937</total_tokens><tool_uses>2</tool_uses><duration_ms>17008</duration_ms></usage>\n</task-notification>"},"uuid":"28dce35b-aedc-4dc0-bc60-5502fe421373","timestamp":"2026-04-23T19:14:28.766Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:14:29.956Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>a48caad27c387cd16</task-id>\n<tool-use-id>toolu_01Jc216enu4HTqt8eFqJKK2L</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a48caad27c387cd16.output</output-file>\n<status>completed</status>\n<summary>Agent \"Session types catalog (capy)\" completed</summary>\n<result>Here is the complete taxonomy across all 32 JSONL session files (3,485 lines, 0 parse errors):\n\n---\n\n**Top-level `type` values**\n\n| type | count |\n|---|---|\n| assistant | 1,691 |\n| user | 1,216 |\n| file-history-snapshot | 215 |\n| attachment | 115 |\n| permission-mode | 99 |\n| system | 87 |\n| last-prompt | 52 |\n| queue-operation | 6 |\n| custom-title | 2 |\n| agent-name | 2 |\n\n---\n\n**`user` message — content block types**\n\n| block type | count |\n|---|---|\n| tool_result | 944 |\n| text (string scalar, not a block) | 237 |\n| text | 35 |\n\nNote: `text(str)` means the `content` field was a plain string rather than an array of blocks — still counted separately.\n\n---\n\n**`assistant` message — content block types**\n\n| block type | count |\n|---|---|\n| tool_use | 944 |\n| text | 433 |\n| thinking | 314 |\n\n---\n\nKey observations:\n\n- Tool-use round-trips dominate: exactly 944 `tool_use` blocks in assistant messages paired with 944 `tool_result` blocks in user messages — a perfect 1:1 match.\n- Extended thinking is heavily used: 314 `thinking` blocks across assistant messages.\n- `file-history-snapshot`, `attachment`, `permission-mode`, and `system` are Claude Code infrastructure types (not conversation content).\n- No `image` blocks appear anywhere in these sessions.</result>\n<usage><total_tokens>13394</total_tokens><tool_uses>2</tool_uses><duration_ms>18260</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:14:34.543Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>a616b05a42c414f0c</task-id>\n<tool-use-id>toolu_015G6xevFdTkv3NkgKm85iWC</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a616b05a42c414f0c.output</output-file>\n<status>completed</status>\n<summary>Agent \"Assistant message structure deep dive\" completed</summary>\n<result>Here is the full taxonomy from 4,529 assistant messages across both projects:\n\n---\n\n**Totals**\n- 4,529 assistant messages total — `content` is ALWAYS an array (never a string)\n- 3 block types found: `tool_use` (2,514), `text` (1,107), `thinking` (909)\n\n---\n\n**Top-level fields on every assistant message** (all 4,529 have these):\n`type`, `message`, `uuid`, `parentUuid`, `isSidechain`, `timestamp`, `userType`, `entrypoint`, `cwd`, `sessionId`, `version`, `gitBranch`\n\nAdditional sparse fields: `requestId` (4,520), `slug` (3,179), `isApiErrorMessage` (9), `error` (1)\n\n---\n\n**Block type taxonomy:**\n\n| Type | Count | Fields |\n|---|---|---|\n| `tool_use` | 2,514 | `type`, `id`, `name`, `input`, `caller` |\n| `text` | 1,107 | `type`, `text` |\n| `thinking` | 909 | `type`, `thinking`, `signature` |\n\n**Key structural findings:**\n\n- **`thinking` blocks** — `{type, thinking, signature}`. The `thinking` field itself is an empty string `\"\"` in all sampled examples — the actual thought content appears to be stripped/redacted, with only the `signature` (a long base64 string) preserved.\n- **`tool_use` blocks** — has an extra `caller` field beyond the standard API fields. `caller` is an object like `{type: \"direct\"}`, not present in the raw Anthropic API response — this is Claude Code's own annotation.\n- **`text` blocks** — exactly `{type, text}`, no extra fields.\n- No other block types (`image`, `document`, `tool_result`, etc.) appear on the assistant side.</result>\n<usage><total_tokens>15110</total_tokens><tool_uses>2</tool_uses><duration_ms>22837</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:14:39.839Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>a7a78d8cd05d0258e</task-id>\n<tool-use-id>toolu_01VR69kdkK8yBRGtLSJHLTGr</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a7a78d8cd05d0258e.output</output-file>\n<status>completed</status>\n<summary>Agent \"Session size and length distribution\" completed</summary>\n<result>Here are the results across 96 sessions (both projects combined):\n\n---\n\n**Distribution Summary**\n\n| Metric | Min | Max | Median | Mean |\n|---|---|---|---|---|\n| size_bytes | 1,988 | 2,596,680 | 61,219 | 362,754 |\n| total_lines | 4 | 705 | 27.5 | 103.8 |\n| user_lines | 1 | 191 | 8.0 | 33.8 |\n| assistant_lines | 0 | 299 | 6.5 | 47.2 |\n| other_lines | 2 | 215 | 8.0 | 22.9 |\n| assistant_text_chars | 0 | 118,789 | 376 | 7,624 |\n\n---\n\n**5 Smallest Sessions (filter candidates)**\n\n| File (UUID) | Chars | User | Asst | Size |\n|---|---|---|---|---|\n| df37c23e... | 0 | 4 | 0 | 4,128 |\n| ef5cdc19... | 0 | 5 | 0 | 4,120 |\n| be970255... | 0 | 2 | 0 | 2,216 |\n| ac33f683... | 0 | 5 | 0 | 4,120 |\n| 80273166... | 0 | 22 | 0 | 18,052 |\n\nNote: all 5 have 0 assistant lines — these are likely interrupted or tool-only sessions.\n\n**5 Largest Sessions**\n\n| File (UUID) | Chars | User | Asst | Size |\n|---|---|---|---|---|\n| 8e252a30... | 118,789 | 191 | 299 | 2,596,680 |\n| d8860e80... | 56,819 | 101 | 170 | 1,164,427 |\n| 9c9d175c... | 33,404 | 98 | 125 | 820,882 |\n| 7d333552... | 31,340 | 109 | 127 | 911,668 |\n| cf3c57c6... | 30,717 | 110 | 189 | 1,137,512 |\n\n---\n\n**Filter result: min 2 turn pairs AND min 200 assistant chars**\n\n- Filtered out: **44 / 96 sessions** (46%)\n- Kept: **52 / 96 sessions** (54%)\n\nThe median of 376 chars is just above the 200-char threshold, so the distribution is right-skewed — many short/empty sessions pulling the median down.</result>\n<usage><total_tokens>14445</total_tokens><tool_uses>3</tool_uses><duration_ms>28115</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:14:40.535Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:14:40.535Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:14:40.535Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"28dce35b-aedc-4dc0-bc60-5502fe421373","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01F8RjwWu4N8ZPSS4g4T1dbQ","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":832,"cache_read_input_tokens":103769,"output_tokens":254,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":832,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEgoq1ucMaWWMK3JfYE","type":"assistant","uuid":"e2c2add7-292e-4556-ab38-950f5c1a7b33","timestamp":"2026-04-23T19:14:38.801Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"e2c2add7-292e-4556-ab38-950f5c1a7b33","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01F8RjwWu4N8ZPSS4g4T1dbQ","type":"message","role":"assistant","content":[{"type":"text","text":"First agent back (toolbox types). Notable new types I hadn't accounted for: `system` (162), `progress` (108), `queue-operation` (20), `custom-title` (6), `agent-name` (6). These are all candidates for filtering out. Waiting for the remaining agents."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":832,"cache_read_input_tokens":103769,"output_tokens":254,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":832,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEgoq1ucMaWWMK3JfYE","type":"assistant","uuid":"254c8399-18be-4998-a4f5-5669102e7193","timestamp":"2026-04-23T19:14:40.037Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"254c8399-18be-4998-a4f5-5669102e7193","isSidechain":false,"promptId":"80a128a5-7d0d-45e7-b256-98520cc2ea58","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>a48caad27c387cd16</task-id>\n<tool-use-id>toolu_01Jc216enu4HTqt8eFqJKK2L</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a48caad27c387cd16.output</output-file>\n<status>completed</status>\n<summary>Agent \"Session types catalog (capy)\" completed</summary>\n<result>Here is the complete taxonomy across all 32 JSONL session files (3,485 lines, 0 parse errors):\n\n---\n\n**Top-level `type` values**\n\n| type | count |\n|---|---|\n| assistant | 1,691 |\n| user | 1,216 |\n| file-history-snapshot | 215 |\n| attachment | 115 |\n| permission-mode | 99 |\n| system | 87 |\n| last-prompt | 52 |\n| queue-operation | 6 |\n| custom-title | 2 |\n| agent-name | 2 |\n\n---\n\n**`user` message — content block types**\n\n| block type | count |\n|---|---|\n| tool_result | 944 |\n| text (string scalar, not a block) | 237 |\n| text | 35 |\n\nNote: `text(str)` means the `content` field was a plain string rather than an array of blocks — still counted separately.\n\n---\n\n**`assistant` message — content block types**\n\n| block type | count |\n|---|---|\n| tool_use | 944 |\n| text | 433 |\n| thinking | 314 |\n\n---\n\nKey observations:\n\n- Tool-use round-trips dominate: exactly 944 `tool_use` blocks in assistant messages paired with 944 `tool_result` blocks in user messages — a perfect 1:1 match.\n- Extended thinking is heavily used: 314 `thinking` blocks across assistant messages.\n- `file-history-snapshot`, `attachment`, `permission-mode`, and `system` are Claude Code infrastructure types (not conversation content).\n- No `image` blocks appear anywhere in these sessions.</result>\n<usage><total_tokens>13394</total_tokens><tool_uses>2</tool_uses><duration_ms>18260</duration_ms></usage>\n</task-notification>"},"uuid":"b4dcfd20-b20e-4139-bb2e-7334b89177af","timestamp":"2026-04-23T19:14:40.552Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"b4dcfd20-b20e-4139-bb2e-7334b89177af","isSidechain":false,"promptId":"80a128a5-7d0d-45e7-b256-98520cc2ea58","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>a616b05a42c414f0c</task-id>\n<tool-use-id>toolu_015G6xevFdTkv3NkgKm85iWC</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a616b05a42c414f0c.output</output-file>\n<status>completed</status>\n<summary>Agent \"Assistant message structure deep dive\" completed</summary>\n<result>Here is the full taxonomy from 4,529 assistant messages across both projects:\n\n---\n\n**Totals**\n- 4,529 assistant messages total — `content` is ALWAYS an array (never a string)\n- 3 block types found: `tool_use` (2,514), `text` (1,107), `thinking` (909)\n\n---\n\n**Top-level fields on every assistant message** (all 4,529 have these):\n`type`, `message`, `uuid`, `parentUuid`, `isSidechain`, `timestamp`, `userType`, `entrypoint`, `cwd`, `sessionId`, `version`, `gitBranch`\n\nAdditional sparse fields: `requestId` (4,520), `slug` (3,179), `isApiErrorMessage` (9), `error` (1)\n\n---\n\n**Block type taxonomy:**\n\n| Type | Count | Fields |\n|---|---|---|\n| `tool_use` | 2,514 | `type`, `id`, `name`, `input`, `caller` |\n| `text` | 1,107 | `type`, `text` |\n| `thinking` | 909 | `type`, `thinking`, `signature` |\n\n**Key structural findings:**\n\n- **`thinking` blocks** — `{type, thinking, signature}`. The `thinking` field itself is an empty string `\"\"` in all sampled examples — the actual thought content appears to be stripped/redacted, with only the `signature` (a long base64 string) preserved.\n- **`tool_use` blocks** — has an extra `caller` field beyond the standard API fields. `caller` is an object like `{type: \"direct\"}`, not present in the raw Anthropic API response — this is Claude Code's own annotation.\n- **`text` blocks** — exactly `{type, text}`, no extra fields.\n- No other block types (`image`, `document`, `tool_result`, etc.) appear on the assistant side.</result>\n<usage><total_tokens>15110</total_tokens><tool_uses>2</tool_uses><duration_ms>22837</duration_ms></usage>\n</task-notification>"},"uuid":"b4fb04e9-c593-4a92-86f8-2dc331321e84","timestamp":"2026-04-23T19:14:40.562Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"b4fb04e9-c593-4a92-86f8-2dc331321e84","isSidechain":false,"promptId":"80a128a5-7d0d-45e7-b256-98520cc2ea58","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>a7a78d8cd05d0258e</task-id>\n<tool-use-id>toolu_01VR69kdkK8yBRGtLSJHLTGr</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a7a78d8cd05d0258e.output</output-file>\n<status>completed</status>\n<summary>Agent \"Session size and length distribution\" completed</summary>\n<result>Here are the results across 96 sessions (both projects combined):\n\n---\n\n**Distribution Summary**\n\n| Metric | Min | Max | Median | Mean |\n|---|---|---|---|---|\n| size_bytes | 1,988 | 2,596,680 | 61,219 | 362,754 |\n| total_lines | 4 | 705 | 27.5 | 103.8 |\n| user_lines | 1 | 191 | 8.0 | 33.8 |\n| assistant_lines | 0 | 299 | 6.5 | 47.2 |\n| other_lines | 2 | 215 | 8.0 | 22.9 |\n| assistant_text_chars | 0 | 118,789 | 376 | 7,624 |\n\n---\n\n**5 Smallest Sessions (filter candidates)**\n\n| File (UUID) | Chars | User | Asst | Size |\n|---|---|---|---|---|\n| df37c23e... | 0 | 4 | 0 | 4,128 |\n| ef5cdc19... | 0 | 5 | 0 | 4,120 |\n| be970255... | 0 | 2 | 0 | 2,216 |\n| ac33f683... | 0 | 5 | 0 | 4,120 |\n| 80273166... | 0 | 22 | 0 | 18,052 |\n\nNote: all 5 have 0 assistant lines — these are likely interrupted or tool-only sessions.\n\n**5 Largest Sessions**\n\n| File (UUID) | Chars | User | Asst | Size |\n|---|---|---|---|---|\n| 8e252a30... | 118,789 | 191 | 299 | 2,596,680 |\n| d8860e80... | 56,819 | 101 | 170 | 1,164,427 |\n| 9c9d175c... | 33,404 | 98 | 125 | 820,882 |\n| 7d333552... | 31,340 | 109 | 127 | 911,668 |\n| cf3c57c6... | 30,717 | 110 | 189 | 1,137,512 |\n\n---\n\n**Filter result: min 2 turn pairs AND min 200 assistant chars**\n\n- Filtered out: **44 / 96 sessions** (46%)\n- Kept: **52 / 96 sessions** (54%)\n\nThe median of 376 chars is just above the 200-char threshold, so the distribution is right-skewed — many short/empty sessions pulling the median down.</result>\n<usage><total_tokens>14445</total_tokens><tool_uses>3</tool_uses><duration_ms>28115</duration_ms></usage>\n</task-notification>"},"uuid":"2e2a6a30-9b0c-4e7d-8b44-33d36511dc18","timestamp":"2026-04-23T19:14:40.570Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"2e2a6a30-9b0c-4e7d-8b44-33d36511dc18","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01DAo8oZy1DsugBPYABmcJ8a","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2430,"cache_read_input_tokens":104601,"output_tokens":427,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2430,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEhgG8GoNY7Yxq812SB","type":"assistant","uuid":"91f34ccf-1574-4765-93fe-86b677ce95d2","timestamp":"2026-04-23T19:14:48.308Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"91f34ccf-1574-4765-93fe-86b677ce95d2","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01DAo8oZy1DsugBPYABmcJ8a","type":"message","role":"assistant","content":[{"type":"text","text":"Three more agents back. Key findings accumulating:\n\n- **Thinking blocks are empty** — the `thinking` field is `\"\"` with only a `signature` (base64). Actual thought content is stripped by Claude Code. Skip these entirely, they have zero indexable content.\n- **Assistant content is always an array**, never a string. Simplifies our parser.\n- **46% of sessions filtered out** by our \"min 2 turn pairs + 200 chars\" heuristic. Good signal-to-noise ratio.\n- Largest session is 2.5 MB / 118K chars of assistant text — we definitely need the chunking strategy.\n\nWaiting on 6 more agents."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2430,"cache_read_input_tokens":104601,"output_tokens":427,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2430,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEhgG8GoNY7Yxq812SB","type":"assistant","uuid":"b54596cf-3267-4085-ad1e-66e72c883051","timestamp":"2026-04-23T19:14:51.360Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:15:09.218Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>ad4f2f55bcf82d098</task-id>\n<tool-use-id>toolu_01HPxhhwPRcCWQzbrYLdDmoU</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad4f2f55bcf82d098.output</output-file>\n<status>completed</status>\n<summary>Agent \"Bare directories investigation\" completed</summary>\n<result>I now have a complete picture. Here is the full report:\n\n---\n\n## Findings: Bare UUID Directories\n\n### 1. Bare Directory Count\n\n- capy project: 8 bare dirs\n- claude-toolbox project: 20 bare dirs\n- Total: 28\n\n### 2. Matching .jsonl Files\n\nEvery bare directory has a corresponding `.jsonl` file with the same UUID name alongside it. No orphaned directories were found (the `db6baad6` case in capy also confirmed its `.jsonl` exists).\n\n### 3. What Is Inside\n\nThe structure is uniform across all 28 directories. Each bare UUID dir contains one or two subdirectories:\n\n**`subagents/` (present in all)**\n\nEach subagent slot contains a pair:\n- `agent-&lt;hex-id&gt;.jsonl` — the full conversation transcript of the sub-agent (same JSONL format as the parent session: `parentUuid`, `isSidechain: true`, `agentId`, `type`, `message`)\n- `agent-&lt;hex-id&gt;.meta.json` — a tiny descriptor, e.g. `{\"agentType\":\"Explore\",\"description\":\"Explore setup command implementation\"}`\n\n**`tool-results/` (rare, only one observed: toolbox `1726ec3b`)**\n\nContains `toolu_&lt;id&gt;.json` — a large JSON array of tool call output (text blobs, file contents returned by MCP tools). This is the cached/stored result of a tool call that was too large to inline into the session JSONL.\n\n### 4. What Are They? (Relationship to Session)\n\nThese are **sub-agent session storage directories**. They are created by Claude Code's Agent tool when a parent session spawns a sub-agent. The bare directory is the storage container for all data generated by sub-agents launched from that parent session. They are NOT related to git worktrees, resumed sessions, or checkpoints.\n\nThe `isSidechain: true` field in every sub-agent JSONL record confirms this — Claude Code marks agent-spawned conversations as side chains off the main session.\n\n### 5. Parseability for Session Content\n\n- `subagents/*.jsonl` — YES, fully parseable as session content. Same schema as top-level `.jsonl` files. Contains the complete turn-by-turn conversation for each sub-agent, including tool calls and responses. Worth parsing if you want full coverage of what happened in a session.\n- `subagents/*.meta.json` — lightweight metadata only (`agentType`, `description`). Useful for indexing/labeling but no conversation content.\n- `tool-results/*.json` — YES, contains tool output payloads that were offloaded from the main JSONL (likely because they exceeded inline size limits). Should be parsed if you need complete tool result data.\n\n### Summary\n\nThese directories are subagent sidecar storage, not metadata-only. If your parser only reads `&lt;uuid&gt;.jsonl` files, it is missing all sub-agent conversation turns. To get full session coverage you must also recurse into `&lt;uuid&gt;/subagents/*.jsonl` and optionally `&lt;uuid&gt;/tool-results/*.json`.</result>\n<usage><total_tokens>33362</total_tokens><tool_uses>5</tool_uses><duration_ms>57503</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:15:09.248Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"b54596cf-3267-4085-ad1e-66e72c883051","isSidechain":false,"promptId":"d700b694-9f22-4364-8a16-3ab3c90e2e90","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>ad4f2f55bcf82d098</task-id>\n<tool-use-id>toolu_01HPxhhwPRcCWQzbrYLdDmoU</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad4f2f55bcf82d098.output</output-file>\n<status>completed</status>\n<summary>Agent \"Bare directories investigation\" completed</summary>\n<result>I now have a complete picture. Here is the full report:\n\n---\n\n## Findings: Bare UUID Directories\n\n### 1. Bare Directory Count\n\n- capy project: 8 bare dirs\n- claude-toolbox project: 20 bare dirs\n- Total: 28\n\n### 2. Matching .jsonl Files\n\nEvery bare directory has a corresponding `.jsonl` file with the same UUID name alongside it. No orphaned directories were found (the `db6baad6` case in capy also confirmed its `.jsonl` exists).\n\n### 3. What Is Inside\n\nThe structure is uniform across all 28 directories. Each bare UUID dir contains one or two subdirectories:\n\n**`subagents/` (present in all)**\n\nEach subagent slot contains a pair:\n- `agent-&lt;hex-id&gt;.jsonl` — the full conversation transcript of the sub-agent (same JSONL format as the parent session: `parentUuid`, `isSidechain: true`, `agentId`, `type`, `message`)\n- `agent-&lt;hex-id&gt;.meta.json` — a tiny descriptor, e.g. `{\"agentType\":\"Explore\",\"description\":\"Explore setup command implementation\"}`\n\n**`tool-results/` (rare, only one observed: toolbox `1726ec3b`)**\n\nContains `toolu_&lt;id&gt;.json` — a large JSON array of tool call output (text blobs, file contents returned by MCP tools). This is the cached/stored result of a tool call that was too large to inline into the session JSONL.\n\n### 4. What Are They? (Relationship to Session)\n\nThese are **sub-agent session storage directories**. They are created by Claude Code's Agent tool when a parent session spawns a sub-agent. The bare directory is the storage container for all data generated by sub-agents launched from that parent session. They are NOT related to git worktrees, resumed sessions, or checkpoints.\n\nThe `isSidechain: true` field in every sub-agent JSONL record confirms this — Claude Code marks agent-spawned conversations as side chains off the main session.\n\n### 5. Parseability for Session Content\n\n- `subagents/*.jsonl` — YES, fully parseable as session content. Same schema as top-level `.jsonl` files. Contains the complete turn-by-turn conversation for each sub-agent, including tool calls and responses. Worth parsing if you want full coverage of what happened in a session.\n- `subagents/*.meta.json` — lightweight metadata only (`agentType`, `description`). Useful for indexing/labeling but no conversation content.\n- `tool-results/*.json` — YES, contains tool output payloads that were offloaded from the main JSONL (likely because they exceeded inline size limits). Should be parsed if you need complete tool result data.\n\n### Summary\n\nThese directories are subagent sidecar storage, not metadata-only. If your parser only reads `&lt;uuid&gt;.jsonl` files, it is missing all sub-agent conversation turns. To get full session coverage you must also recurse into `&lt;uuid&gt;/subagents/*.jsonl` and optionally `&lt;uuid&gt;/tool-results/*.json`.</result>\n<usage><total_tokens>33362</total_tokens><tool_uses>5</tool_uses><duration_ms>57503</duration_ms></usage>\n</task-notification>"},"uuid":"a29847f9-72f8-48a9-9133-5e4c94287bea","timestamp":"2026-04-23T19:15:09.260Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"last-prompt","lastPrompt":"Looks good, but have you thorougly explored the jsonl files and are confident what we keep vs what we drop? You can use @~/.claude/projects/-home-sergio-Projects-personal-capy and @~/.claude/projects/…","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"permission-mode","permissionMode":"default","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"a29847f9-72f8-48a9-9133-5e4c94287bea","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01U1GrmBow4ULC2bdCfdqVPW","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1400,"cache_read_input_tokens":107031,"output_tokens":407,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1400,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEjo6CLwFaiYXSHBGsm","type":"assistant","uuid":"4ece8c45-836b-4d41-82f3-f5d5db7d60c6","timestamp":"2026-04-23T19:15:18.142Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"4ece8c45-836b-4d41-82f3-f5d5db7d60c6","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01U1GrmBow4ULC2bdCfdqVPW","type":"message","role":"assistant","content":[{"type":"text","text":"Important discovery from the bare directories agent: those directories contain **sub-agent conversations**. Each has `subagents/*.jsonl` files with full conversation transcripts (same JSONL schema), plus `*.meta.json` with agent type/description. There's also a rare `tool-results/` dir for offloaded large tool outputs.\n\nThis means if we only parse top-level `.jsonl` files, we miss sub-agent work — which is often where detailed research and implementation happens. We'll need to decide whether to include sub-agent conversations. I'll hold that question until all agents report back."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1400,"cache_read_input_tokens":107031,"output_tokens":407,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1400,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEjo6CLwFaiYXSHBGsm","type":"assistant","uuid":"680bb795-fe13-4231-9882-5c79bedcf5e5","timestamp":"2026-04-23T19:15:20.638Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:15:23.847Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>ad24cff58eef19977</task-id>\n<tool-use-id>toolu_01RD4eZaK4uHfny7CjWQ1wnP</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad24cff58eef19977.output</output-file>\n<status>completed</status>\n<summary>Agent \"User message structure deep dive\" completed</summary>\n<result>Script written to `/home/sergio/Projects/personal/capy/analyze_user_messages.py`.\n\n---\n\nHere is the full taxonomy from 96 files / 3,246 user messages:\n\n**Top-level fields on user messages**\n\n| Field | Count | Notes |\n|---|---|---|\n| `uuid`, `parentUuid`, `sessionId`, `type`, `message`, `timestamp`, `userType`, `entrypoint`, `cwd`, `version`, `gitBranch`, `isSidechain` | 3246 (ALL) | Always present |\n| `promptId` | 3024 (93%) | Absent on tool-result injection messages |\n| `toolUseResult` | 2514 (77%) | Co-present with `sourceToolAssistantUUID` — the structured tool output |\n| `sourceToolAssistantUUID` | 2514 (77%) | UUID of the assistant turn that issued the tool call |\n| `slug` | 2170 (66%) | Short human-readable session label |\n| `permissionMode` | 372 (11%) | |\n| `isMeta` | 158 (4%) | |\n| `sourceToolUseID` | 44 (1%) | |\n| `mcpMeta` | 17 (&lt;1%) | Always `{structuredContent: ...}` — MCP structured output |\n| `origin` | 7 (&lt;1%) | |\n\n**Content type**\n- `string` — 649 (19%): direct human text, `message.content` is a plain string\n- `array` — 2597 (80%): block array, `message.content` is `[{type, ...}, ...]`\n\n**Array block types**\n- `tool_result` — 2514 occurrences\n- `text` — 83 occurrences (interruptions, injected skill instructions)\n\n**tool_result block fields**\n- Always: `type`, `tool_use_id`, `content`\n- Optional: `is_error` (555 occurrences, 22%)\n\n**tool_result `.content` shape**\n- `nested_string` — 2224 (raw text output)\n- `nested_array` — 290 (structured MCP results), containing:\n  - `text` blocks — 252\n  - `tool_reference` blocks — 103 (keys: `type`, `tool_name`)\n\n**`toolUseResult` shapes (top 5)**\n- `{file, type}` — 727x (Read/Write results)\n- `{stdout, stderr, interrupted, isImage, noOutputExpected}` — 470x (Bash)\n- `{filePath, newString, oldString, originalFile, replaceAll, structuredPatch, userModified}` — 447x (Edit)\n- `list` — 178x\n- `{statusChange, success, taskId, updatedFields, verificationNudgeNeeded}` — 112x (task tools)</result>\n<usage><total_tokens>22725</total_tokens><tool_uses>4</tool_uses><duration_ms>72138</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:15:23.876Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"680bb795-fe13-4231-9882-5c79bedcf5e5","isSidechain":false,"promptId":"0908cc7b-d437-4fc8-b49c-6e0f776cd8b9","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>ad24cff58eef19977</task-id>\n<tool-use-id>toolu_01RD4eZaK4uHfny7CjWQ1wnP</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ad24cff58eef19977.output</output-file>\n<status>completed</status>\n<summary>Agent \"User message structure deep dive\" completed</summary>\n<result>Script written to `/home/sergio/Projects/personal/capy/analyze_user_messages.py`.\n\n---\n\nHere is the full taxonomy from 96 files / 3,246 user messages:\n\n**Top-level fields on user messages**\n\n| Field | Count | Notes |\n|---|---|---|\n| `uuid`, `parentUuid`, `sessionId`, `type`, `message`, `timestamp`, `userType`, `entrypoint`, `cwd`, `version`, `gitBranch`, `isSidechain` | 3246 (ALL) | Always present |\n| `promptId` | 3024 (93%) | Absent on tool-result injection messages |\n| `toolUseResult` | 2514 (77%) | Co-present with `sourceToolAssistantUUID` — the structured tool output |\n| `sourceToolAssistantUUID` | 2514 (77%) | UUID of the assistant turn that issued the tool call |\n| `slug` | 2170 (66%) | Short human-readable session label |\n| `permissionMode` | 372 (11%) | |\n| `isMeta` | 158 (4%) | |\n| `sourceToolUseID` | 44 (1%) | |\n| `mcpMeta` | 17 (&lt;1%) | Always `{structuredContent: ...}` — MCP structured output |\n| `origin` | 7 (&lt;1%) | |\n\n**Content type**\n- `string` — 649 (19%): direct human text, `message.content` is a plain string\n- `array` — 2597 (80%): block array, `message.content` is `[{type, ...}, ...]`\n\n**Array block types**\n- `tool_result` — 2514 occurrences\n- `text` — 83 occurrences (interruptions, injected skill instructions)\n\n**tool_result block fields**\n- Always: `type`, `tool_use_id`, `content`\n- Optional: `is_error` (555 occurrences, 22%)\n\n**tool_result `.content` shape**\n- `nested_string` — 2224 (raw text output)\n- `nested_array` — 290 (structured MCP results), containing:\n  - `text` blocks — 252\n  - `tool_reference` blocks — 103 (keys: `type`, `tool_name`)\n\n**`toolUseResult` shapes (top 5)**\n- `{file, type}` — 727x (Read/Write results)\n- `{stdout, stderr, interrupted, isImage, noOutputExpected}` — 470x (Bash)\n- `{filePath, newString, oldString, originalFile, replaceAll, structuredPatch, userModified}` — 447x (Edit)\n- `list` — 178x\n- `{statusChange, success, taskId, updatedFields, verificationNudgeNeeded}` — 112x (task tools)</result>\n<usage><total_tokens>22725</total_tokens><tool_uses>4</tool_uses><duration_ms>72138</duration_ms></usage>\n</task-notification>"},"uuid":"6c04fdf9-f9a5-4942-8ec4-be9bf30acd0d","timestamp":"2026-04-23T19:15:23.899Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:15:27.049Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>ae5e6c1956e56c56e</task-id>\n<tool-use-id>toolu_01AdEQ1jLZFyDyiyc6W63nDs</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ae5e6c1956e56c56e.output</output-file>\n<status>completed</status>\n<summary>Agent \"Slash commands and noise patterns\" completed</summary>\n<result>Here is the full analysis report:\n\n---\n\n**Files processed:** 96 (32 capy + 64 toolbox)\n**Total user messages:** 3,245\n\n---\n\n**Q3 — Tool-result-only messages (pure noise, 77.5%)**\n2,514 messages contain only `tool_result` blocks with zero human text. These are automatic SDK returns after tool calls. Always skip.\n\n**Q1 — Slash commands**\nZero found. They are either pre-stripped before being stored, or this user does not type `/compact`, `/clear`, etc. as raw turns.\n\n**Q2 — Short messages (&lt; 20 chars, 125 total)**\nAlmost all are low-information confirmations or navigation picks:\n- `yes` / `Yes` (40x), `Proceed` (3x), `looks good` / `Looks good` (4x) — approval noise\n- `1`, `2`, `3`, `A`, `B`, `C` (12x) — menu selection noise\n- `Let's commit` / `Commit` / `Commit please` (13x) — commit triggers\n- `run pal listmodels`, `run bash ls` — micro-commands\n\n**Q4 / Q6 — system-reminder content**\n- 1 message had `&lt;system-reminder&gt;` inside a `type:text` block. It was a skill-injected preamble (the `claude-api` skill content), not a human turn.\n- 0 occurrences in other block types.\n- Conclusion: system-reminder appears almost exclusively injected by skills/tools into text blocks, not typed by humans.\n\n**Q5 — Noise vs Signal breakdown**\n\n| Category | Count | % |\n|---|---|---|\n| Tool-result only (SKIP) | 2,514 | 77.5% |\n| Slash commands (SKIP) | 0 | 0% |\n| Short &lt; 20 chars (review) | 125 | 3.9% |\n| Empty text (SKIP) | 0 | 0% |\n| **Signal — real human input (KEEP)** | **606** | **18.7%** |\n\n---\n\n**Filtering heuristics to implement:**\n\n1. SKIP if all content blocks are `tool_result` (no `text` blocks)\n2. SKIP if `full_text` starts with `/`\n3. SKIP if `full_text` is empty after joining `text` blocks\n4. SKIP (or flag) if a `type:text` block contains `&lt;system-reminder&gt;` — it is injected context\n5. REVIEW if `len(full_text) &lt; 20` — likely confirmations/picks, low signal value\n6. KEEP everything else — genuine task/query messages\n\n**Script written to:** `/home/sergio/Projects/personal/capy/analyze_user_messages.py`\nRun with `python analyze_user_messages.py` or pass `--dirs` for other project folders.</result>\n<usage><total_tokens>20350</total_tokens><tool_uses>5</tool_uses><duration_ms>75323</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:15:29.918Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>acb8ca54b83b68f7d</task-id>\n<tool-use-id>toolu_01R4mW5Vn1yFdijcDrLQQj6F</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/acb8ca54b83b68f7d.output</output-file>\n<status>completed</status>\n<summary>Agent \"Special message types analysis\" completed</summary>\n<result>Script written. Here is the full analysis:\n\n---\n\n**Actions taken:**\n- Processed all 96 JSONL files (9,964 lines, 0 parse errors) across both project dirs\n- Analyzed every non-user/non-assistant record: types, keys, subtypes, examples\n- Written script to `/home/sergio/Projects/personal/capy/analyze_jsonl_types.py`\n\n---\n\n**All 9 non-user/non-assistant types found:**\n\n| type | count | keys |\n|---|---|---|\n| `file-history-snapshot` | 651 | messageId, snapshot, isSnapshotUpdate |\n| `attachment` | 450 | attachment, uuid, timestamp, sessionId, cwd, gitBranch, parentUuid, isSidechain, … |\n| `permission-mode` | 416 | permissionMode, sessionId |\n| `last-prompt` | 275 | lastPrompt, sessionId |\n| `system` | 249 | type, subtype, content, durationMs, messageCount, uuid, timestamp, … |\n| `progress` | 108 | data, toolUseID, parentToolUseID, timestamp, … |\n| `queue-operation` | 29 | operation (enqueue/dequeue), content, timestamp |\n| `custom-title` | 8 | customTitle, sessionId |\n| `agent-name` | 8 | agentName, sessionId |\n\n**`attachment` sub-types (13 total):**\n`task_reminder` (104), `hook_success` (97), `hook_additional_context` (75), `mcp_instructions_delta` (64), `deferred_tools_delta` (37), `skill_listing` (22), `command_permissions` (22), `directory` (19), `file` (3), `queued_command` (3), `plan_mode_exit` (2), `edited_text_file` (1), `plan_mode` (1)\n\n**`system` sub-types (3 total):**\n- `turn_duration` (183) — timing metadata only (`durationMs`, `messageCount`)\n- `local_command` (55) — stdout of slash-commands like `/reload-plugins`\n- `away_summary` (11) — **the compaction/summary analogue**: free-text recap paragraph written when the user returns after being away. This is the closest thing to a \"context compaction marker\" — carries full session state summary in the `content` field\n\n**On compaction:** There is NO dedicated `summary`, `compact`, or `context-compaction` type. Context compaction is API-internal and leaves no distinct JSONL record. `system/away_summary` is the only human-readable session digest.\n\n**Content vs metadata split:** Types carrying actual conversational content: `system/away_summary`, `system/local_command`, `attachment/queued_command`, `attachment/hook_additional_context`, `attachment/task_reminder`, `attachment/file`, `attachment/directory`, `last-prompt`, `queue-operation`. Pure metadata: everything else (`file-history-snapshot`, `permission-mode`, `custom-title`, `agent-name`, `system/turn_duration`, `progress`, and the delta attachment subtypes).</result>\n<usage><total_tokens>28262</total_tokens><tool_uses>5</tool_uses><duration_ms>78207</duration_ms></usage>\n</task-notification>"}
 {"parentUuid":"6c04fdf9-f9a5-4942-8ec4-be9bf30acd0d","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NpwtpgKZ8hT57PEcwzSgMu","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1337,"cache_read_input_tokens":108431,"output_tokens":513,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1337,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEkscqPW8VAL58umTjr","type":"assistant","uuid":"5e13fee6-46da-461a-9d33-3c2e7a50dcfd","timestamp":"2026-04-23T19:15:32.930Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"5e13fee6-46da-461a-9d33-3c2e7a50dcfd","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NpwtpgKZ8hT57PEcwzSgMu","type":"message","role":"assistant","content":[{"type":"text","text":"User message deep dive confirms: 80% of user messages are tool result arrays, only 19% are direct human text. The `toolUseResult` top-level field is Claude Code's structured annotation — separate from `message.content`. We skip both tool_result blocks and toolUseResult entirely.\n\nInteresting finding: 83 `text` blocks appear *inside* user arrays alongside tool_results — described as \"interruptions, injected skill instructions.\" Need to decide if those carry signal or noise.\n\nLet me clean up that analysis script the agent created."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1337,"cache_read_input_tokens":108431,"output_tokens":513,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1337,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEkscqPW8VAL58umTjr","type":"assistant","uuid":"67de6632-d309-4426-b908-a880ad1d399a","timestamp":"2026-04-23T19:15:36.220Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"67de6632-d309-4426-b908-a880ad1d399a","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01NpwtpgKZ8hT57PEcwzSgMu","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AgSWU2Y9LmdGEXynTYqBET","name":"Bash","input":{"command":"rm -f /home/sergio/Projects/personal/capy/analyze_user_messages.py","description":"Remove temp analysis script"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1337,"cache_read_input_tokens":108431,"output_tokens":513,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1337,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEkscqPW8VAL58umTjr","type":"assistant","uuid":"26e96431-be7e-4b0b-be02-f90b5bc07da9","timestamp":"2026-04-23T19:15:36.589Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"26e96431-be7e-4b0b-be02-f90b5bc07da9","isSidechain":false,"attachment":{"type":"hook_blocking_error","hookName":"PreToolUse:Bash","toolUseID":"toolu_01AgSWU2Y9LmdGEXynTYqBET","hookEvent":"PreToolUse","blockingError":{"blockingError":"Blocked by security policy: matches deny pattern Bash(rm:*)","command":"bash $CLAUDE_PROJECT_DIR/.claude/scripts/capy.sh hook pretooluse"}},"type":"attachment","uuid":"8be9fe33-b5e6-4d6f-a2f6-aa1d55f4cc41","timestamp":"2026-04-23T19:15:36.624Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"26e96431-be7e-4b0b-be02-f90b5bc07da9","isSidechain":false,"promptId":"0908cc7b-d437-4fc8-b49c-6e0f776cd8b9","type":"user","message":{"role":"user","content":[{"type":"tool_result","content":"Blocked by security policy: matches deny pattern Bash(rm:*)","is_error":true,"tool_use_id":"toolu_01AgSWU2Y9LmdGEXynTYqBET"}]},"uuid":"9cde410b-a733-464b-a637-6ecdcb13e8d0","timestamp":"2026-04-23T19:15:36.654Z","toolUseResult":"Error: Blocked by security policy: matches deny pattern Bash(rm:*)","sourceToolAssistantUUID":"26e96431-be7e-4b0b-be02-f90b5bc07da9","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"remove","timestamp":"2026-04-23T19:15:36.671Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"queue-operation","operation":"remove","timestamp":"2026-04-23T19:15:36.671Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"9cde410b-a733-464b-a637-6ecdcb13e8d0","isSidechain":false,"attachment":{"type":"queued_command","prompt":"<task-notification>\n<task-id>ae5e6c1956e56c56e</task-id>\n<tool-use-id>toolu_01AdEQ1jLZFyDyiyc6W63nDs</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ae5e6c1956e56c56e.output</output-file>\n<status>completed</status>\n<summary>Agent \"Slash commands and noise patterns\" completed</summary>\n<result>Here is the full analysis report:\n\n---\n\n**Files processed:** 96 (32 capy + 64 toolbox)\n**Total user messages:** 3,245\n\n---\n\n**Q3 — Tool-result-only messages (pure noise, 77.5%)**\n2,514 messages contain only `tool_result` blocks with zero human text. These are automatic SDK returns after tool calls. Always skip.\n\n**Q1 — Slash commands**\nZero found. They are either pre-stripped before being stored, or this user does not type `/compact`, `/clear`, etc. as raw turns.\n\n**Q2 — Short messages (&lt; 20 chars, 125 total)**\nAlmost all are low-information confirmations or navigation picks:\n- `yes` / `Yes` (40x), `Proceed` (3x), `looks good` / `Looks good` (4x) — approval noise\n- `1`, `2`, `3`, `A`, `B`, `C` (12x) — menu selection noise\n- `Let's commit` / `Commit` / `Commit please` (13x) — commit triggers\n- `run pal listmodels`, `run bash ls` — micro-commands\n\n**Q4 / Q6 — system-reminder content**\n- 1 message had `&lt;system-reminder&gt;` inside a `type:text` block. It was a skill-injected preamble (the `claude-api` skill content), not a human turn.\n- 0 occurrences in other block types.\n- Conclusion: system-reminder appears almost exclusively injected by skills/tools into text blocks, not typed by humans.\n\n**Q5 — Noise vs Signal breakdown**\n\n| Category | Count | % |\n|---|---|---|\n| Tool-result only (SKIP) | 2,514 | 77.5% |\n| Slash commands (SKIP) | 0 | 0% |\n| Short &lt; 20 chars (review) | 125 | 3.9% |\n| Empty text (SKIP) | 0 | 0% |\n| **Signal — real human input (KEEP)** | **606** | **18.7%** |\n\n---\n\n**Filtering heuristics to implement:**\n\n1. SKIP if all content blocks are `tool_result` (no `text` blocks)\n2. SKIP if `full_text` starts with `/`\n3. SKIP if `full_text` is empty after joining `text` blocks\n4. SKIP (or flag) if a `type:text` block contains `&lt;system-reminder&gt;` — it is injected context\n5. REVIEW if `len(full_text) &lt; 20` — likely confirmations/picks, low signal value\n6. KEEP everything else — genuine task/query messages\n\n**Script written to:** `/home/sergio/Projects/personal/capy/analyze_user_messages.py`\nRun with `python analyze_user_messages.py` or pass `--dirs` for other project folders.</result>\n<usage><total_tokens>20350</total_tokens><tool_uses>5</tool_uses><duration_ms>75323</duration_ms></usage>\n</task-notification>","commandMode":"task-notification"},"type":"attachment","uuid":"e9b3a2a8-a1a1-4ecf-9b8f-6172dc10dec1","timestamp":"2026-04-23T19:15:36.671Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"e9b3a2a8-a1a1-4ecf-9b8f-6172dc10dec1","isSidechain":false,"attachment":{"type":"queued_command","prompt":"<task-notification>\n<task-id>acb8ca54b83b68f7d</task-id>\n<tool-use-id>toolu_01R4mW5Vn1yFdijcDrLQQj6F</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/acb8ca54b83b68f7d.output</output-file>\n<status>completed</status>\n<summary>Agent \"Special message types analysis\" completed</summary>\n<result>Script written. Here is the full analysis:\n\n---\n\n**Actions taken:**\n- Processed all 96 JSONL files (9,964 lines, 0 parse errors) across both project dirs\n- Analyzed every non-user/non-assistant record: types, keys, subtypes, examples\n- Written script to `/home/sergio/Projects/personal/capy/analyze_jsonl_types.py`\n\n---\n\n**All 9 non-user/non-assistant types found:**\n\n| type | count | keys |\n|---|---|---|\n| `file-history-snapshot` | 651 | messageId, snapshot, isSnapshotUpdate |\n| `attachment` | 450 | attachment, uuid, timestamp, sessionId, cwd, gitBranch, parentUuid, isSidechain, … |\n| `permission-mode` | 416 | permissionMode, sessionId |\n| `last-prompt` | 275 | lastPrompt, sessionId |\n| `system` | 249 | type, subtype, content, durationMs, messageCount, uuid, timestamp, … |\n| `progress` | 108 | data, toolUseID, parentToolUseID, timestamp, … |\n| `queue-operation` | 29 | operation (enqueue/dequeue), content, timestamp |\n| `custom-title` | 8 | customTitle, sessionId |\n| `agent-name` | 8 | agentName, sessionId |\n\n**`attachment` sub-types (13 total):**\n`task_reminder` (104), `hook_success` (97), `hook_additional_context` (75), `mcp_instructions_delta` (64), `deferred_tools_delta` (37), `skill_listing` (22), `command_permissions` (22), `directory` (19), `file` (3), `queued_command` (3), `plan_mode_exit` (2), `edited_text_file` (1), `plan_mode` (1)\n\n**`system` sub-types (3 total):**\n- `turn_duration` (183) — timing metadata only (`durationMs`, `messageCount`)\n- `local_command` (55) — stdout of slash-commands like `/reload-plugins`\n- `away_summary` (11) — **the compaction/summary analogue**: free-text recap paragraph written when the user returns after being away. This is the closest thing to a \"context compaction marker\" — carries full session state summary in the `content` field\n\n**On compaction:** There is NO dedicated `summary`, `compact`, or `context-compaction` type. Context compaction is API-internal and leaves no distinct JSONL record. `system/away_summary` is the only human-readable session digest.\n\n**Content vs metadata split:** Types carrying actual conversational content: `system/away_summary`, `system/local_command`, `attachment/queued_command`, `attachment/hook_additional_context`, `attachment/task_reminder`, `attachment/file`, `attachment/directory`, `last-prompt`, `queue-operation`. Pure metadata: everything else (`file-history-snapshot`, `permission-mode`, `custom-title`, `agent-name`, `system/turn_duration`, `progress`, and the delta attachment subtypes).</result>\n<usage><total_tokens>28262</total_tokens><tool_uses>5</tool_uses><duration_ms>78207</duration_ms></usage>\n</task-notification>","commandMode":"task-notification"},"type":"attachment","uuid":"867a7738-39ad-4d87-950a-ba38aebe8874","timestamp":"2026-04-23T19:15:36.671Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:15:41.218Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>a5c523c552380c08b</task-id>\n<tool-use-id>toolu_015joRcwrnRtWsGyKYRgSRNS</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a5c523c552380c08b.output</output-file>\n<status>completed</status>\n<summary>Agent \"Tool usage metadata extraction\" completed</summary>\n<result>I need Bash permission to write the file. Let me present the full findings and script inline instead.\n\n---\n\nHere are the complete findings from analyzing 96 .jsonl files (33.2 MB) across both project directories:\n\n---\n\n## Key Findings\n\n**1. Frequency table — all 25 unique tools**\n\n| Count | Tool name |\n|------:|-----------|\n| 749 | Read |\n| 504 | Bash |\n| 463 | Edit |\n| 115 | TaskUpdate |\n| 99 | Grep |\n| 78 | Glob |\n| 74 | Write |\n| 67 | ToolSearch |\n| 65 | TaskCreate |\n| 51 | Agent |\n| 45 | Skill |\n| 41 | mcp__capy__capy_fetch_and_index |\n| 37 | mcp__capy__capy_search |\n| 31 | mcp__pal__codereview |\n| 27 | mcp__capy__capy_index |\n| 15 | mcp__pal__listmodels |\n| 13 | mcp__capy__capy_batch_execute |\n| 11 | mcp__serena__get_symbols_overview |\n| 8 | mcp__pal__chat |\n| 7 | mcp__capy__capy_execute |\n| 6 | mcp__serena__find_symbol |\n| 4 | ExitPlanMode |\n| 2 | EnterPlanMode |\n| 2 | mcp__context7__query-docs |\n| 1 | mcp__context7__resolve-library-id |\n\n**2. Block structure (every single tool_use block has identical shape)**\n\n```\ntool_use block keys: ['caller', 'id', 'input', 'name', 'type']\n```\nNo exceptions — all 25 tools, all 2514 blocks share these exact 5 keys.\n\n**3. Field path — canonical and unambiguous**\n\n```\nmessage.content[i].name   where message.content[i].type == \"tool_use\"\n```\nNo variants found. `name` is always there, always at that path.\n\n**4. Tool_use blocks per assistant message**\n- 2018 messages: 0 blocks\n- 2515 messages: exactly 1 block\n- **Never more than 1** — these sessions show single-tool-call-per-turn behavior\n- Avg across all assistant messages: 0.555\n- Avg across messages that have any tool_use: **1.000**\n\n**5. Nested content in `input` fields** — these tools carry list/dict values inside `input`:\n\n| Tool | Nested input keys |\n|------|-------------------|\n| ExitPlanMode | `allowedPrompts` (list) |\n| mcp__capy__capy_batch_execute | `commands`, `queries` (lists) |\n| mcp__capy__capy_search | `queries` (list) |\n| mcp__pal__chat | `absolute_file_paths` (list) |\n| mcp__pal__codereview | `relevant_files` (list) |\n\n**6. BM25 chunk title recommendation**\n\n- Extract from: `message.content[i].name` (type-gated on `tool_use`)\n- Format: plain string, no parsing needed\n- MCP tools follow `mcp__&lt;server&gt;__&lt;tool&gt;` — you can index the full name OR split on `__` to index server (`capy`, `pal`, `serena`, `context7`) and tool name separately for better recall\n- Top 10 tools cover ~98% of all calls; `Read`, `Bash`, `Edit` alone cover ~68%\n\n---\n\nThe script I need Bash write permission to save to `/home/sergio/Projects/personal/capy/docs/analyze_tool_use.py` — please allow Bash or grant write access and I'll persist it immediately. The full script content is ready.</result>\n<usage><total_tokens>19668</total_tokens><tool_uses>8</tool_uses><duration_ms>89497</duration_ms></usage>\n</task-notification>"}
 {"type":"last-prompt","lastPrompt":"Looks good, but have you thorougly explored the jsonl files and are confident what we keep vs what we drop? You can use @~/.claude/projects/-home-sergio-Projects-personal-capy and @~/.claude/projects/…","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"permission-mode","permissionMode":"default","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:15:57.239Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"867a7738-39ad-4d87-950a-ba38aebe8874","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01GNVHNADhcgYaWpWkF42GMw","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2638,"cache_read_input_tokens":109768,"output_tokens":838,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2638,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEmpCizxB6Djs85Lkv2","type":"assistant","uuid":"5406d2d1-987c-400f-9aa9-ed3fb72e7423","timestamp":"2026-04-23T19:15:49.642Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"5406d2d1-987c-400f-9aa9-ed3fb72e7423","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01GNVHNADhcgYaWpWkF42GMw","type":"message","role":"assistant","content":[{"type":"text","text":"Two critical findings from the latest agents:\n\n**Slash commands don't appear in stored sessions at all** — zero found across 96 files. Either Claude Code strips them before writing to JSONL or handles them before they become messages. Our `/` filter is still worth having defensively, but it won't fire in practice.\n\n**`system/away_summary` is the compaction equivalent** — 11 occurrences, free-text recap paragraphs written when the user returns after being away. These are dense session state summaries. We should keep these. There is NO dedicated compact/summary type — context compaction is API-internal and leaves no JSONL record.\n\n**Noise breakdown confirmed**: 77.5% of user messages are pure tool_result returns (skip), only 18.7% are real human input. Short messages like \"yes\", \"looks good\" (3.9%) are low-signal individually but I'd keep them — the assistant response following \"yes, proceed\" is often where the decision is articulated.\n\nUpdated filtering rules based on findings:\n- Skip `tool_result`-only user messages (no text blocks)\n- Skip `system/turn_duration`, `system/local_command`\n- Keep `system/away_summary` — high-signal summaries\n- Skip all `attachment`, `file-history-snapshot`, `permission-mode`, `progress`, `queue-operation`, `custom-title`, `agent-name`, `last-prompt`\n- Skip `thinking` blocks (content is empty/stripped, only signature remains)\n- Filter `<system-reminder>` tags from text blocks if present\n\nStill waiting on 2 agents: edge cases and tool usage metadata."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2638,"cache_read_input_tokens":109768,"output_tokens":838,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2638,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEmpCizxB6Djs85Lkv2","type":"assistant","uuid":"bf448cae-79b1-4ce2-bef7-0ff2f693f4fb","timestamp":"2026-04-23T19:15:57.127Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"bf448cae-79b1-4ce2-bef7-0ff2f693f4fb","isSidechain":false,"type":"system","subtype":"turn_duration","durationMs":33326,"messageCount":232,"timestamp":"2026-04-23T19:15:57.231Z","uuid":"a4c485b2-b434-457f-92d8-1928a446d349","isMeta":false,"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"a4c485b2-b434-457f-92d8-1928a446d349","isSidechain":false,"promptId":"bcf20770-b3d4-4a3b-925f-7c96e8cc3b7e","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>a5c523c552380c08b</task-id>\n<tool-use-id>toolu_015joRcwrnRtWsGyKYRgSRNS</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/a5c523c552380c08b.output</output-file>\n<status>completed</status>\n<summary>Agent \"Tool usage metadata extraction\" completed</summary>\n<result>I need Bash permission to write the file. Let me present the full findings and script inline instead.\n\n---\n\nHere are the complete findings from analyzing 96 .jsonl files (33.2 MB) across both project directories:\n\n---\n\n## Key Findings\n\n**1. Frequency table — all 25 unique tools**\n\n| Count | Tool name |\n|------:|-----------|\n| 749 | Read |\n| 504 | Bash |\n| 463 | Edit |\n| 115 | TaskUpdate |\n| 99 | Grep |\n| 78 | Glob |\n| 74 | Write |\n| 67 | ToolSearch |\n| 65 | TaskCreate |\n| 51 | Agent |\n| 45 | Skill |\n| 41 | mcp__capy__capy_fetch_and_index |\n| 37 | mcp__capy__capy_search |\n| 31 | mcp__pal__codereview |\n| 27 | mcp__capy__capy_index |\n| 15 | mcp__pal__listmodels |\n| 13 | mcp__capy__capy_batch_execute |\n| 11 | mcp__serena__get_symbols_overview |\n| 8 | mcp__pal__chat |\n| 7 | mcp__capy__capy_execute |\n| 6 | mcp__serena__find_symbol |\n| 4 | ExitPlanMode |\n| 2 | EnterPlanMode |\n| 2 | mcp__context7__query-docs |\n| 1 | mcp__context7__resolve-library-id |\n\n**2. Block structure (every single tool_use block has identical shape)**\n\n```\ntool_use block keys: ['caller', 'id', 'input', 'name', 'type']\n```\nNo exceptions — all 25 tools, all 2514 blocks share these exact 5 keys.\n\n**3. Field path — canonical and unambiguous**\n\n```\nmessage.content[i].name   where message.content[i].type == \"tool_use\"\n```\nNo variants found. `name` is always there, always at that path.\n\n**4. Tool_use blocks per assistant message**\n- 2018 messages: 0 blocks\n- 2515 messages: exactly 1 block\n- **Never more than 1** — these sessions show single-tool-call-per-turn behavior\n- Avg across all assistant messages: 0.555\n- Avg across messages that have any tool_use: **1.000**\n\n**5. Nested content in `input` fields** — these tools carry list/dict values inside `input`:\n\n| Tool | Nested input keys |\n|------|-------------------|\n| ExitPlanMode | `allowedPrompts` (list) |\n| mcp__capy__capy_batch_execute | `commands`, `queries` (lists) |\n| mcp__capy__capy_search | `queries` (list) |\n| mcp__pal__chat | `absolute_file_paths` (list) |\n| mcp__pal__codereview | `relevant_files` (list) |\n\n**6. BM25 chunk title recommendation**\n\n- Extract from: `message.content[i].name` (type-gated on `tool_use`)\n- Format: plain string, no parsing needed\n- MCP tools follow `mcp__&lt;server&gt;__&lt;tool&gt;` — you can index the full name OR split on `__` to index server (`capy`, `pal`, `serena`, `context7`) and tool name separately for better recall\n- Top 10 tools cover ~98% of all calls; `Read`, `Bash`, `Edit` alone cover ~68%\n\n---\n\nThe script I need Bash write permission to save to `/home/sergio/Projects/personal/capy/docs/analyze_tool_use.py` — please allow Bash or grant write access and I'll persist it immediately. The full script content is ready.</result>\n<usage><total_tokens>19668</total_tokens><tool_uses>8</tool_uses><duration_ms>89497</duration_ms></usage>\n</task-notification>"},"uuid":"5fef43f3-c657-40e7-bdcd-b60546eec410","timestamp":"2026-04-23T19:15:57.254Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"5fef43f3-c657-40e7-bdcd-b60546eec410","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PVHGKQkwrPsoF2pSjPLfmM","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"","signature":"Es8HClkIDRgCKkA2MGeJ+Qwwo2ntHUJq6Hb1j1lMkNaXfVLkEVhqla0e+p72GGzEeLntbToDp5WVsPVicMc4YcoYNaDa8FvLG8T/Mg9jbGF1ZGUtb3B1cy00LTY4ABIMA0ta4BPcq2mJ/AVhGgwZOaRIo+OiHE6vcWgiMH2LwZ1StWZVZggJhpEZTfBldtpLVl369h2A1ZaO1gWmmmNEUZr76rGDx0GBmigQ0SqjBjJpc8woemVj7G8d2VkMSi0py9rLgI8U8nMFQO9riiPM3vn8nsZo1itgJT5wFQc0ECNa8N9K+oFxonuPMnmj14iBDkjFfAiWWfgu3UcXmimNYMURpRJp/J2fP1rcXfweK1OU5TmNBE0XkIuHqvzrYAHmoP9be6ZIHvj+ZUFp4VcNGiMNOAFb5EqkT8ppTeues68aFpKxA3c50Za6pVQoqdwDFypCNvoueAutIp3V0+r/O2LRaUrd7C3P1+iKtoz4YSukH+bbgSX5nmjNXWbQ4ESYuFzOkcZglsAdMPUf/aRPShVC88P/R/Sby2qOoKwvmNBjTDI96A7nkOe03bQ5CKLD4gVX2QwxCC4z4nrUIr+ANV5xVQ+cAMPwc5jLeVfyNXWZVFBz4WcD10LFab9qvV0vGYpowrKo0aowf1iaVh8mJ+crbTHzFEUQ9M6woangcWerwulA5ia7nnk++vT0U2DKUcxBVVpQj5h2dK/NNPrpMIw2amA3ua35LdDC2qZp3bFWucF4GCraKXnk7NGt4CAHwM06hMRYzCoiQ9pxl55GU6CYG922rkC34wd8VKTJr9W3z0ZSPeZY+XFJeFdULi2+1rnCXsz4ZG8NTAnrYtAl4HJU7LWs294pSWzoVL2lHXZJQBtln/6R5jGUzvpiIEIZIJC+PlRadabt9z/DQ4V1MHvryaxzyzuNbATOdPPfLos+LhUgStBIliUTrbRqcoQQoMharMF/E3XazKZLTnzQT5pLQ2QOXUfGlsxGmyYQr3ZRnSKwj/uaGyoYhl1t4oNQU3wmzX6COeI2bCsIuSQkCfqLSFZDASt6LLQwNPRDBK3SigAOS7kgTXUjGxQubgF0um1ngruNwh592xZqJ0M/XFS9EJbEqFF8LEV+4wqbf7Cw8SSXheehj0tIQIEVCBtBbYzPu74DcJqrNdcbd+CXYR5iCYj3trzLhNKgFwhOHm+eacKGKDfkZ1M3nM/+LjDUuKrsf00j5PI8afTZoeF8EgWBZXPFMDKm+Xpr73OJCLN+yZYCBjTI9l2PWubjmrUFY8C3Muzff2dAs5afZMBGApp8GAE="}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2027,"cache_read_input_tokens":112406,"output_tokens":362,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2027,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEoLBK1rj3ASPfXGLrf","type":"assistant","uuid":"c4b149da-2341-4301-8ea7-f5f6902e60ba","timestamp":"2026-04-23T19:16:04.322Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"c4b149da-2341-4301-8ea7-f5f6902e60ba","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01PVHGKQkwrPsoF2pSjPLfmM","type":"message","role":"assistant","content":[{"type":"text","text":"Tool metadata agent back. Clean results:\n\n- **25 unique tools**, always at `message.content[i].name` — no variants\n- **Exactly 1 tool_use per assistant message** — never more. Simplifies extraction.\n- Top 3 (Read/Bash/Edit) cover 68% of all calls\n- MCP tools follow `mcp__<server>__<tool>` convention — we could normalize to `capy:search` etc. in chunk titles for better BM25 recall\n\nOne agent remaining: edge cases."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":2027,"cache_read_input_tokens":112406,"output_tokens":362,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2027,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEoLBK1rj3ASPfXGLrf","type":"assistant","uuid":"7ab69cdd-d2ee-4ce3-b2b9-391157b95908","timestamp":"2026-04-23T19:16:05.673Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"queue-operation","operation":"enqueue","timestamp":"2026-04-23T19:16:59.867Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","content":"<task-notification>\n<task-id>ab34b1b13cd33756b</task-id>\n<tool-use-id>toolu_01676oJccvGAMBe4NggEfkzU</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ab34b1b13cd33756b.output</output-file>\n<status>completed</status>\n<summary>Agent \"Edge case sessions analysis\" completed</summary>\n<result>Script written and validated. Here's the summary:\n\n**File created:** `/home/sergio/Projects/personal/capy/analyze_edge_cases.py`\nA self-contained script with CLI flags (`--dirs`, `--gap-hours`) that prints the full edge-case report.\n\n---\n\n**Key findings across 96 sessions:**\n\n| # | Category | Count | Notes |\n|---|---|---|---|\n| 6 | Malformed JSON | **0** | All files parse cleanly |\n| 1 | 0–1 user messages | **2** | `3648dd3c` (1 msg, skill invocation, aborted) · `3806f26c` (\"hi\", got reply) |\n| 2 | Config-only `/` sessions | **0** | No such pattern exists |\n| 3 | No assistant text blocks | **1** | `3648dd3c` — assistant entry exists but only has a `thinking` block, no `text` |\n| 4 | Resumed sessions | **25** | Identified by perm-mode &gt;2 OR timestamp gap &gt;8h. Worst case: `8e252a30` (56 perm-mode entries!) |\n| 5 | Tool-result-only user turns | **0** | All sessions have at least one human text turn |\n| 7 | Compaction events | **2** | `7c713c7d` and `fdd75d40` — \"compacted\" keyword found in a `user`-type entry's message |\n\n**Critical insight discovered:** 2 permission-mode entries is Claude Code's normal startup pattern (initial + reset). Only &gt;2 signals a true session resume. This corrected the original false-positive count from 91 down to 25 meaningful sessions.</result>\n<usage><total_tokens>33345</total_tokens><tool_uses>9</tool_uses><duration_ms>168149</duration_ms></usage>\n</task-notification>"}
 {"type":"queue-operation","operation":"dequeue","timestamp":"2026-04-23T19:16:59.899Z","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"7ab69cdd-d2ee-4ce3-b2b9-391157b95908","isSidechain":false,"promptId":"538ba8d6-cab6-4f25-841d-542867cf4fed","type":"user","message":{"role":"user","content":"<task-notification>\n<task-id>ab34b1b13cd33756b</task-id>\n<tool-use-id>toolu_01676oJccvGAMBe4NggEfkzU</tool-use-id>\n<output-file>/tmp/claude-1000/-home-sergio-Projects-personal-capy/b5ee5362-8700-4c9c-8278-51cb58c2e096/tasks/ab34b1b13cd33756b.output</output-file>\n<status>completed</status>\n<summary>Agent \"Edge case sessions analysis\" completed</summary>\n<result>Script written and validated. Here's the summary:\n\n**File created:** `/home/sergio/Projects/personal/capy/analyze_edge_cases.py`\nA self-contained script with CLI flags (`--dirs`, `--gap-hours`) that prints the full edge-case report.\n\n---\n\n**Key findings across 96 sessions:**\n\n| # | Category | Count | Notes |\n|---|---|---|---|\n| 6 | Malformed JSON | **0** | All files parse cleanly |\n| 1 | 0–1 user messages | **2** | `3648dd3c` (1 msg, skill invocation, aborted) · `3806f26c` (\"hi\", got reply) |\n| 2 | Config-only `/` sessions | **0** | No such pattern exists |\n| 3 | No assistant text blocks | **1** | `3648dd3c` — assistant entry exists but only has a `thinking` block, no `text` |\n| 4 | Resumed sessions | **25** | Identified by perm-mode &gt;2 OR timestamp gap &gt;8h. Worst case: `8e252a30` (56 perm-mode entries!) |\n| 5 | Tool-result-only user turns | **0** | All sessions have at least one human text turn |\n| 7 | Compaction events | **2** | `7c713c7d` and `fdd75d40` — \"compacted\" keyword found in a `user`-type entry's message |\n\n**Critical insight discovered:** 2 permission-mode entries is Claude Code's normal startup pattern (initial + reset). Only &gt;2 signals a true session resume. This corrected the original false-positive count from 91 down to 25 meaningful sessions.</result>\n<usage><total_tokens>33345</total_tokens><tool_uses>9</tool_uses><duration_ms>168149</duration_ms></usage>\n</task-notification>"},"uuid":"6beb217d-1416-4391-a86a-9bcef93439f2","timestamp":"2026-04-23T19:16:59.916Z","permissionMode":"default","origin":{"kind":"task-notification"},"userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"05f41512-cdc2-4f7c-bf30-aa6156bde3d8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01CBmctiWdCfmDLpNpvJu9nd","type":"message","role":"assistant","content":[{"type":"text","text":"All 10 agents are back. Let me synthesize the complete picture.\n\n---\n\n**Complete JSONL format taxonomy — what to KEEP vs SKIP:**\n\n| Record type | Decision | Reason |\n|---|---|---|\n| `user` (string content) | **KEEP** | Direct human input |\n| `user` (text blocks in array) | **KEEP** | Human text, strip `<system-reminder>` tags |\n| `user` (tool_result only) | **SKIP** | Automatic SDK returns, no human content |\n| `assistant` text blocks | **KEEP** | Core conversational content |\n| `assistant` thinking blocks | **SKIP** | Content stripped, only signature remains |\n| `assistant` tool_use blocks | **EXTRACT name only** | Tool names go in chunk title metadata |\n| `system/away_summary` | **KEEP** | Dense session recap, high signal |\n| `system/turn_duration` | **SKIP** | Timing metadata |\n| `system/local_command` | **SKIP** | Slash command stdout |\n| `attachment` (all subtypes) | **SKIP** | Infrastructure metadata |\n| `file-history-snapshot` | **SKIP** | File backup metadata |\n| `permission-mode` | **SKIP** (but count for resume detection) | Startup metadata |\n| `progress` | **SKIP** | Progress indicators |\n| `queue-operation` | **SKIP** | Queue metadata |\n| `custom-title`, `agent-name` | **SKIP** | Session labels |\n| `last-prompt` | **SKIP** | UI state |\n\n**Key corrections to our earlier assumptions:**\n\n1. **Thinking blocks are useless** — content is stripped, only base64 signature remains\n2. **No slash commands in stored JSONL** — `/` filter is defensive only\n3. **Compaction has no dedicated type** — `system/away_summary` is closest, plus 2 sessions had \"compacted\" in user entries\n4. **Sub-agent conversations** exist in `<uuid>/subagents/*.jsonl` — same schema, parseable\n5. **25 of 96 sessions are resumed** (>2 permission-mode entries) — our mtime gate + full re-index handles this\n6. **Always exactly 1 tool_use per assistant message** — extraction is trivial\n\nAlso, some agents left temp scripts in the project directory — I'll clean those up after we finish the design.\n\nNow, one new question from the bare directories finding: **should we index sub-agent conversations?** Sub-agents do research, exploration, and implementation work. That's high-value content. But it adds complexity (recursing into directories, handling `isSidechain: true`). I'd include them in the parent session's source — same label, additional turns appended to the transcript. Thoughts?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":993,"cache_read_input_tokens":114433,"output_tokens":1177,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":993,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMEsx5fdamXUjLK3ZaDu","type":"assistant","uuid":"a395c9b0-a66f-489f-bee5-3366268939c8","timestamp":"2026-04-23T19:17:27.005Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"file-history-snapshot","messageId":"45dbec87-6f51-49e8-8edc-e8c755ca54a6","snapshot":{"messageId":"45dbec87-6f51-49e8-8edc-e8c755ca54a6","trackedFileBackups":{},"timestamp":"2026-04-23T19:21:19.968Z"},"isSnapshotUpdate":false}
 {"parentUuid":"a395c9b0-a66f-489f-bee5-3366268939c8","isSidechain":false,"promptId":"2d45b987-5889-4143-9e37-7dd65d90257c","type":"user","message":{"role":"user","content":"agree, agents sub-sessions carry imporant context, and yes, they should be in parrent session's source (maybe with an additional label indicating it comes from subagent?)"},"uuid":"45dbec87-6f51-49e8-8edc-e8c755ca54a6","timestamp":"2026-04-23T19:21:19.952Z","permissionMode":"default","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"c25ab8fb-f55b-4a69-90f3-6ece91fc1c18","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_011oyVR6izMsr28zHnjJg1jb","type":"message","role":"assistant","content":[{"type":"text","text":"Good. Sub-agent turns get a marker in the transcript like:\n\n```\n--- Subagent: Explore — \"Explore setup command implementation\" ---\nHuman: ...\nAssistant: ...\n--- End subagent ---\n```\n\nThe agent type and description come from `meta.json`. This makes sub-agent context searchable — \"explore setup command\" would match. Chunk titles can also include `Subagent: Explore` when the window contains sub-agent turns.\n\nLet me continue the design sections. We have all the data we need now.\n\n---\n\n**Section 3: Chunking Strategy**\n\nSession transcripts are converted to a plaintext format before chunking. Each turn becomes:\n\n```\nHuman: <text>\nAssistant: <text>\n[Tools: Read, Edit, Bash]\n```\n\nTool-result-only user messages are omitted. `system/away_summary` entries are inserted inline as `[Session summary: <text>]`. Sub-agent conversations are delimited with `--- Subagent: <type> — \"<description>\" ---` and `--- End subagent ---` markers.\n\nChunking uses a sliding window of ~4 turn pairs with 1-pair overlap, adapted from `chunkPlainText`. The split happens on turn boundaries (the `Human:` prefix), not arbitrary line counts. This preserves conversational coherence — a question and its answer always stay together.\n\nEach chunk gets a title: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Tools: Read, Edit`. When the window contains sub-agent turns, the title appends `| Subagent: Explore`. MCP tool names are normalized from `mcp__capy__capy_search` to `capy:search` for readability.\n\nChunks exceeding `maxChunkBytes` (4096) are split at paragraph boundaries using the existing `splitOversized` logic. The overlap ensures continuity: if a decision spans two chunks, the overlapping turn appears in both, so BM25 can surface either.\n\nThe content type is `\"session\"` — a new value added to the content type taxonomy alongside `\"code\"`, `\"prose\"`, `\"plaintext\"`, `\"markdown\"`, `\"json\"`.\n\n---\n\nDoes this look right?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":1225,"cache_read_input_tokens":115426,"output_tokens":791,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1225,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMFD7tYq29YBZTkwJtAC","type":"assistant","uuid":"094fb105-11e4-4aaf-9b6b-77aa876ac54a","timestamp":"2026-04-23T19:21:41.351Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"e0ad0890-bdd5-4053-bcb3-04f1d4c0331e","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01G5bMEH7kKKWaa5Z3bkHTpM","type":"message","role":"assistant","content":[{"type":"text","text":"Noted — MCP tool names stay as-is (`mcp__capy__capy_search`, not normalized).\n\n---\n\n**Section 4: Storage — KindSession, Schema, and Cleanup**\n\nA new `KindSession` source kind is added alongside `KindDurable` and `KindEphemeral`. This requires:\n\n**Schema migration**: The `sources` table CHECK constraint changes from `CHECK (kind IN ('ephemeral', 'durable'))` to `CHECK (kind IN ('ephemeral', 'durable', 'session'))`. Added via `applyMigrations` in `migrate.go`, following the existing migration pattern.\n\n**types.go**: Add `KindSession SourceKind = \"session\"`. Update `Valid()` to accept it. Add `\"session\"` as a content type constant.\n\n**Cleanup**: Sessions use strict TTL (like ephemeral), not retention scoring (like durable). `cleanupEphemeral` is generalized to accept a kind+TTL pair — it becomes `cleanupByTTL(kind SourceKind, ttl time.Duration)`. `Cleanup()` calls it twice: once for ephemeral (24h default), once for session (60 days default). The logic is identical — `indexed_at < cutoff` — just different TTL and kind values.\n\n**Config**: `CleanupConfig` gains `SessionTTLDays int` (default 60, minimum 1). Validated at load time like `EphemeralTTLHours`.\n\n**Search**: Sessions are included in default search results. `SearchOptions.IncludeKinds` default changes from `[durable]` to `[durable, session]`. Users can exclude sessions via `include_kinds: [\"durable\"]` if desired.\n\n**Stats**: `StoreStats` gains `SessionSourceCount`, `SessionFreshCount`, `SessionStaleCount` — same fresh/stale bucketing as ephemeral, based on the session TTL.\n\n---\n\nSound right?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":927,"cache_read_input_tokens":116651,"output_tokens":548,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":927,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMFQbUnM3k9P2A16JkNB","type":"assistant","uuid":"b30b80b7-5579-4c26-9f22-4e5aa080f388","timestamp":"2026-04-23T19:24:11.756Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"b9033baf-cf8b-4735-a716-66a4b66d8d09","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01YGE22uj24gtNDwof18NBVA","type":"message","role":"assistant","content":[{"type":"text","text":"---\n\n**Section 5: Session Discovery and Sweep Mechanism**\n\nSession indexing is triggered at MCP server startup as a background goroutine. The sweep runs once per server boot — not continuously.\n\n**Discovery**: Claude Code stores sessions in `~/.claude/projects/<dir-name>/` where `<dir-name>` is the absolute project path with `/` replaced by `-` and leading `-` (e.g. `-home-sergio-Projects-personal-capy`). The server already knows `projectDir` — it derives the session directory by mangling that path the same way Claude Code does, then verifying the directory exists.\n\n**Sweep algorithm**:\n1. List all `.jsonl` files in the session directory\n2. For each file, `stat()` to get mtime\n3. Query the store for a source with label `session:<datetime>:<uuid>` — but since we don't know the datetime before parsing, we need a different mtime gate. Instead: query all sources with `session:` prefix, build a map of `uuid → indexed_at`. Compare file mtime against `indexed_at`. If mtime <= indexed_at, skip.\n4. For files that pass the mtime gate: parse JSONL, apply filtering, build transcript, compute content_hash\n5. Call `Index()` with the session label, content type `\"session\"`, and `KindSession`. Existing dedup handles the rest.\n6. For sessions with sub-agent directories (`<uuid>/subagents/*.jsonl`): parse sub-agent files and append to the parent transcript before chunking.\n\n**Current session exclusion**: The session that just started will have a near-empty JSONL file. It passes through the sweep but gets filtered out by the session-level gate (< 2 turn pairs).\n\n**Error handling**: Parse failures on individual sessions are logged and skipped — one corrupt file doesn't block the sweep. The goroutine has a timeout (30s default) to avoid blocking startup indefinitely.\n\n---\n\nDoes this look right?"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":710,"cache_read_input_tokens":118149,"output_tokens":477,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":710,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMFe4bob2Jfepjgubzsm","type":"assistant","uuid":"1a94dd10-31ed-4ce8-ab7f-928c21c0c384","timestamp":"2026-04-23T19:27:13.843Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"13799599-9a73-406a-be9f-ac87e361e587","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01DaoXEwipKjgC6qmv1EpE3d","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013NtMuDsaxBErACoNMeUcDS","name":"mcp__pal__chat","input":{"prompt":"Continuing our sessionflow RAG discussion. I need your review of the sweep algorithm we've designed for session discovery and indexing.\n\n**Context recap:**\n- Sessions are indexed at MCP server startup (background goroutine, not in hooks)\n- Session files live in `~/.claude/projects/<dir-name>/` where `<dir-name>` is the project path with `/` replaced by `-`\n- Labels are machine-agnostic: `session:2026-04-05T12:06:26Z:102ad512-759a-43ad-8805-353ce341f65c`\n- Sub-agent conversations live in `<uuid>/subagents/*.jsonl` alongside the parent `.jsonl`\n\n**The sweep algorithm:**\n\n1. Derive the session directory by mangling `projectDir` the same way Claude Code does (replace `/` with `-`), look for it under `~/.claude/projects/`\n2. List all `.jsonl` files in that directory\n3. For each file, `stat()` to get mtime\n4. Query all existing sources with `session:` label prefix from the store, build a map of `uuid → indexed_at` timestamp\n5. Compare file mtime against `indexed_at`. If mtime <= indexed_at, skip (already indexed, unchanged)\n6. For files that pass the mtime gate: parse JSONL, apply filtering (skip tool_result-only user messages, skip thinking blocks, extract tool names from tool_use, keep system/away_summary, strip system-reminder tags), build transcript\n7. Apply session-level gate: min 2 meaningful turn pairs + min 200 chars assistant text. Skip if not met.\n8. For sessions with sub-agent directories (`<uuid>/subagents/*.jsonl`): parse sub-agent files, read their `meta.json` for type/description, append to parent transcript with delimiters\n9. Compute content_hash of the filtered transcript\n10. Call `Index()` with label `session:<datetime>:<uuid>`, content type `\"session\"`, kind `KindSession`. Existing dedup (content_hash check) handles already-indexed-but-mtime-changed cases.\n11. Current (just-started) session is near-empty, filtered out by session-level gate.\n\n**Error handling:** Parse failures on individual sessions are logged and skipped. The goroutine has a 30s timeout.\n\n**My concerns:**\n\nA. **Step 4 is O(n) in stored sources** — we query all `session:` prefixed sources to build the uuid→indexed_at map. With hundreds of sessions over months, is this a problem? The query is `SELECT label, indexed_at FROM sources WHERE label LIKE 'session:%'` — no index on label by default.\n\nB. **The mtime gate has a subtle issue**: the label contains the datetime, so we can't look up a source by UUID alone — we need the full label. But we don't know the datetime until we parse the file. Should we use the filename (UUID) as a secondary lookup key? Or store the UUID separately?\n\nC. **Sub-agent directory detection**: we check for `<uuid>/subagents/` existence. If the directory exists but the parent `.jsonl` hasn't changed (mtime gate passes), we'd skip re-indexing. But what if only a sub-agent file changed? Is that possible, or does the parent JSONL always get updated when sub-agents run?\n\nD. **Race condition**: the current session's JSONL is being written to while we sweep. Could we read a partial file? Should we skip the file whose UUID matches the current session ID?\n\nE. **The 30s timeout**: is this enough for a first-time sweep of 50+ sessions? Each file needs parsing, filtering, chunking, and SQLite indexing.\n\nPoke holes. What am I missing?","model":"gemini-3.1-pro-preview","thinking_mode":"high","temperature":0.3,"continuation_id":"02160141-215e-4d68-9a4c-85d6bd844b4b","absolute_file_paths":["/home/sergio/Projects/personal/capy/internal/store/index.go","/home/sergio/Projects/personal/capy/internal/store/store.go","/home/sergio/Projects/personal/capy/internal/server/server.go","/home/sergio/Projects/personal/capy/internal/config/paths.go"],"working_directory_absolute_path":"/home/sergio/Projects/personal/capy"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":10,"cache_creation_input_tokens":504,"cache_read_input_tokens":118859,"output_tokens":1210,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":504,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMFmgYUYSuA2Yzr1R6cA","type":"assistant","uuid":"d38b89f3-2d7f-40ab-8413-2cc3a8289130","timestamp":"2026-04-23T19:29:06.667Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"d38b89f3-2d7f-40ab-8413-2cc3a8289130","isSidechain":false,"promptId":"d11f0b78-86bf-457d-bf00-4fbeb4abe537","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013NtMuDsaxBErACoNMeUcDS","type":"tool_result","content":[{"type":"text","text":"{\"status\":\"continuation_available\",\"content\":\"This is a very well-thought-out ingestion pipeline. The mtime gate and background goroutine approach perfectly balances performance with the constraints of the MCP lifecycle. \\n\\nHere is my review of your concerns, along with a few minor course corrections to keep things robust.\\n\\n### A. Step 4 O(n) query performance\\n**Verdict: Not a problem. Don't over-engineer an index yet.**\\nA full table scan in SQLite for a few thousand rows takes fractions of a millisecond. Since this runs once in a background goroutine at startup, an O(n) scan on the `sources` table is completely negligible. \\n*Recommendation:* Stick with `SELECT label, indexed_at FROM sources WHERE label LIKE 'session:%'`. If profiling later shows this taking more than 50ms (highly unlikely), you can add an index on `label`, but avoid the schema migration for now.\\n\\n### B. The mtime gate & label format\\n**Verdict: Handle it in Go, not in SQL.**\\nYou don't need a secondary lookup key or a schema change. When you execute the query from Step 4, you'll get back rows of `(label, indexed_at)`. \\n*Recommendation:* As you iterate over the `sql.Rows` in Go, simply split the label:\\n```go\\nparts := strings.Split(label, \\\":\\\")\\nif len(parts) == 3 {\\n    uuid := parts[2]\\n    mtimeMap[uuid] = indexedAt\\n}\\n```\\nThen, when iterating over the `.jsonl` files on disk, strip the `.jsonl` extension to get the UUID and do an O(1) map lookup.\\n\\n### C. Sub-agent directory detection\\n**Verdict: Parent mtime is unreliable; check the directory.**\\nWhile a parent session *usually* updates when a sub-agent returns, relying on that is risky.\\n*Recommendation:* When evaluating the mtime for a session, compute the `max()` of the parent `.jsonl` file's mtime AND the `subagents/` directory's mtime. `os.Stat` on a directory updates when files are added or removed inside it. \\n```go\\nsessionMtime := parentFileInfo.ModTime()\\nif subDirInfo, err := os.Stat(filepath.Join(dir, uuid, \\\"subagents\\\")); err == nil {\\n    if subDirInfo.ModTime().After(sessionMtime) {\\n        sessionMtime = subDirInfo.ModTime()\\n    }\\n}\\n```\\n\\n### D. Race condition with the current session\\n**Verdict: JSONL's line-oriented nature saves you here.**\\nBecause JSONL is append-only, reading it concurrently is generally safe. The only risk is reading a half-written JSON string on the very last line.\\n*Recommendation:* When parsing the JSONL, if `json.Unmarshal` fails on a specific line, just log a debug message and `continue` to the next line (or EOF). Because of your session-level gate (min 2 meaningful turn pairs), the current active session will almost certainly be skipped anyway. You don't need complex logic to explicitly identify and skip the active session ID.\\n\\n### E. The 30s timeout\\n**Verdict: 30 seconds is massive overkill (in a good way).**\\nGo's JSON decoder is incredibly fast, and SQLite in WAL mode can handle tens of thousands of inserts per second. Even if you have 50 sessions that *all* bypass the mtime gate (e.g., on first run), reading a few megabytes of JSONL and executing 50 transactions will likely complete in under 2 seconds. \\n*Recommendation:* Keep the 30s context timeout as a safety net against unforeseen deadlocks, but don't worry about hitting it.\\n\\n### F. One New Gotcha: Project Directory Mangling\\nYou mentioned: *\\\"Derive the session directory by mangling `projectDir`... (replace `/` with `-`)\\\"*.\\nBe very careful here. Claude Code's project directory naming convention in `~/.claude/projects/` is often a combination of the base folder name and a hash to prevent collisions (e.g., `myproject-a1b2c3d4`). \\n*Recommendation:* Verify Claude Code's exact path generation logic. You may need to read `~/.claude/projects.json` (if it exists) to map the current absolute `projectDir` to the correct Claude Code session storage directory, rather than just doing a string replace.\\n\\n***\\n\\nYour algorithm is solid and ready to implement. The mtime map built in Go and the max-mtime check for sub-agents will make this extremely efficient.\\n\\nPlease respond using the continuation_id from this response - your input is needed to proceed. Let me know how you want to handle the Claude Code directory resolution (Gotcha F), and we can move on to the implementation!\\n\\n---\\n\\nAGENT'S TURN: Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand.\",\"content_type\":\"text\",\"metadata\":{\"tool_name\":\"chat\",\"conversation_ready\":true,\"model_used\":\"gemini-3.1-pro-preview\",\"provider_used\":\"google\"},\"continuation_offer\":{\"continuation_id\":\"02160141-215e-4d68-9a4c-85d6bd844b4b\",\"note\":\"You can continue this conversation for 41 more exchanges.\",\"remaining_turns\":41}}"}]}]},"uuid":"048ea97e-1403-490f-a813-73cdf02def13","timestamp":"2026-04-23T19:29:37.642Z","toolUseResult":[{"type":"text","text":"{\"status\":\"continuation_available\",\"content\":\"This is a very well-thought-out ingestion pipeline. The mtime gate and background goroutine approach perfectly balances performance with the constraints of the MCP lifecycle. \\n\\nHere is my review of your concerns, along with a few minor course corrections to keep things robust.\\n\\n### A. Step 4 O(n) query performance\\n**Verdict: Not a problem. Don't over-engineer an index yet.**\\nA full table scan in SQLite for a few thousand rows takes fractions of a millisecond. Since this runs once in a background goroutine at startup, an O(n) scan on the `sources` table is completely negligible. \\n*Recommendation:* Stick with `SELECT label, indexed_at FROM sources WHERE label LIKE 'session:%'`. If profiling later shows this taking more than 50ms (highly unlikely), you can add an index on `label`, but avoid the schema migration for now.\\n\\n### B. The mtime gate & label format\\n**Verdict: Handle it in Go, not in SQL.**\\nYou don't need a secondary lookup key or a schema change. When you execute the query from Step 4, you'll get back rows of `(label, indexed_at)`. \\n*Recommendation:* As you iterate over the `sql.Rows` in Go, simply split the label:\\n```go\\nparts := strings.Split(label, \\\":\\\")\\nif len(parts) == 3 {\\n    uuid := parts[2]\\n    mtimeMap[uuid] = indexedAt\\n}\\n```\\nThen, when iterating over the `.jsonl` files on disk, strip the `.jsonl` extension to get the UUID and do an O(1) map lookup.\\n\\n### C. Sub-agent directory detection\\n**Verdict: Parent mtime is unreliable; check the directory.**\\nWhile a parent session *usually* updates when a sub-agent returns, relying on that is risky.\\n*Recommendation:* When evaluating the mtime for a session, compute the `max()` of the parent `.jsonl` file's mtime AND the `subagents/` directory's mtime. `os.Stat` on a directory updates when files are added or removed inside it. \\n```go\\nsessionMtime := parentFileInfo.ModTime()\\nif subDirInfo, err := os.Stat(filepath.Join(dir, uuid, \\\"subagents\\\")); err == nil {\\n    if subDirInfo.ModTime().After(sessionMtime) {\\n        sessionMtime = subDirInfo.ModTime()\\n    }\\n}\\n```\\n\\n### D. Race condition with the current session\\n**Verdict: JSONL's line-oriented nature saves you here.**\\nBecause JSONL is append-only, reading it concurrently is generally safe. The only risk is reading a half-written JSON string on the very last line.\\n*Recommendation:* When parsing the JSONL, if `json.Unmarshal` fails on a specific line, just log a debug message and `continue` to the next line (or EOF). Because of your session-level gate (min 2 meaningful turn pairs), the current active session will almost certainly be skipped anyway. You don't need complex logic to explicitly identify and skip the active session ID.\\n\\n### E. The 30s timeout\\n**Verdict: 30 seconds is massive overkill (in a good way).**\\nGo's JSON decoder is incredibly fast, and SQLite in WAL mode can handle tens of thousands of inserts per second. Even if you have 50 sessions that *all* bypass the mtime gate (e.g., on first run), reading a few megabytes of JSONL and executing 50 transactions will likely complete in under 2 seconds. \\n*Recommendation:* Keep the 30s context timeout as a safety net against unforeseen deadlocks, but don't worry about hitting it.\\n\\n### F. One New Gotcha: Project Directory Mangling\\nYou mentioned: *\\\"Derive the session directory by mangling `projectDir`... (replace `/` with `-`)\\\"*.\\nBe very careful here. Claude Code's project directory naming convention in `~/.claude/projects/` is often a combination of the base folder name and a hash to prevent collisions (e.g., `myproject-a1b2c3d4`). \\n*Recommendation:* Verify Claude Code's exact path generation logic. You may need to read `~/.claude/projects.json` (if it exists) to map the current absolute `projectDir` to the correct Claude Code session storage directory, rather than just doing a string replace.\\n\\n***\\n\\nYour algorithm is solid and ready to implement. The mtime map built in Go and the max-mtime check for sub-agents will make this extremely efficient.\\n\\nPlease respond using the continuation_id from this response - your input is needed to proceed. Let me know how you want to handle the Claude Code directory resolution (Gotcha F), and we can move on to the implementation!\\n\\n---\\n\\nAGENT'S TURN: Evaluate this perspective alongside your analysis to form a comprehensive solution and continue with the user's request and task at hand.\",\"content_type\":\"text\",\"metadata\":{\"tool_name\":\"chat\",\"conversation_ready\":true,\"model_used\":\"gemini-3.1-pro-preview\",\"provider_used\":\"google\"},\"continuation_offer\":{\"continuation_id\":\"02160141-215e-4d68-9a4c-85d6bd844b4b\",\"note\":\"You can continue this conversation for 41 more exchanges.\",\"remaining_turns\":41}}"}],"sourceToolAssistantUUID":"d38b89f3-2d7f-40ab-8413-2cc3a8289130","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"048ea97e-1403-490f-a813-73cdf02def13","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_019cXUJAPFSopx6GaP6a4MWb","type":"message","role":"assistant","content":[{"type":"text","text":"PAL validated the sweep algorithm and raised good points:\n\n**A. O(n) query — not a problem.** `SELECT ... WHERE label LIKE 'session:%'` on a few thousand rows is sub-millisecond. No index needed.\n\n**B. UUID lookup from label — solve in Go.** Split the label string `session:<datetime>:<uuid>` to extract UUID, build an in-memory map. O(1) lookup per file.\n\n**C. Sub-agent mtime — good catch.** Don't rely on parent mtime alone. Take `max(parent.mtime, subagents_dir.mtime)` so changes to sub-agent files trigger re-indexing.\n\n**D. Race condition — JSONL saves us.** Append-only format means partial reads only affect the last line. Just skip lines that fail `json.Unmarshal`. The session-level gate filters out the near-empty active session anyway.\n\n**E. 30s timeout — plenty.** Even a cold-start sweep of 50+ sessions would finish in ~2 seconds. 30s is a safety net.\n\n**F. Directory mangling — needs verification.** PAL flagged that Claude Code's naming might not be a simple `/` → `-` replacement. We already observed the actual format (`-home-sergio-Projects-personal-capy`), which IS the path with `/` replaced by `-`. But we should verify there's no hash suffix or other variation. Let me quick-check that."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":2559,"cache_read_input_tokens":119363,"output_tokens":421,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2559,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMFqoeUL1JW3VLwNvtah","type":"assistant","uuid":"aea50f5b-f54d-46d5-8589-f1ef7e9de03f","timestamp":"2026-04-23T19:29:47.920Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"559718ee-97a8-4750-a6f7-7fd47f07f216","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01WrNfpx5UdE9D9ix6J9pPZi","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01XwMKhUTS3RMbAucujPkYMY","name":"Write","input":{"file_path":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","content":"# Sessionflow RAG — Design Document\n\n> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n> **Status:** Draft\n> **Created:** 2026-04-23\n\n## Problem\n\nClaude Code stores conversation sessions as JSONL files in `~/.claude/projects/<project-dir-name>/`. These sessions contain valuable decisions, rationale, and context that is lost after conversations end. capy already solves context flooding and provides persistent queryable memory, but only for content explicitly indexed during a session — the conversations themselves are invisible to future searches.\n\n## Solution\n\nSessionflow RAG makes past sessions automatically searchable by indexing their human/assistant text content into capy's FTS5 knowledge base. A background sweep runs at MCP server startup, parsing session JSONL files, filtering out noise, chunking the conversational text into BM25-friendly windows, and indexing them under a new `KindSession` source kind.\n\nThe feature is entirely automatic — no MCP tool is exposed, the assistant never needs to think about it, and the indexed content stays portable across machines by using machine-agnostic labels (session UUID + datetime, not file paths).\n\n## Design Decisions\n\n### Source Kind: `KindSession`\n\nA new source kind alongside `KindDurable` and `KindEphemeral`. Sessions have a distinct lifecycle: they are not transient command output (ephemeral) nor explicitly curated knowledge (durable). They represent conversational history with a natural decay curve measured in weeks/months.\n\n- **Cleanup:** Strict TTL (default 60 days, configurable via `session_ttl_days`), same mechanism as ephemeral. Access count is ignored — sessions decay by age, not usage frequency.\n- **Search:** Included in default search results alongside durable content. Users can exclude via `include_kinds: [\"durable\"]`.\n- **Stats:** Reported separately with fresh/stale TTL bucketing.\n\n### Indexing Trigger: MCP Server Startup\n\nIndexing runs as a background goroutine fired during `Server.Serve()`. This was chosen over alternatives:\n\n- **Session-end hook** — rejected. The hook is a short-lived process; goroutines die when it exits. Also risks DB lock contention with the dying MCP server (see `internal/hook/sessionend.go` WAL warning).\n- **Session-start hook** — rejected for the same lifecycle reason (short-lived process).\n- **MCP server startup** — chosen. The server is a long-lived process with safe DB access. A background goroutine doesn't block Claude Code's UI. The 1-2 second delay before the previous session becomes searchable is invisible.\n\nTrade-off: one-session delay before content is searchable. Acceptable because you never search the current session.\n\n### Session Directory Discovery\n\nClaude Code stores sessions in `~/.claude/projects/<dir-name>/` where `<dir-name>` is the absolute project path with `/` and `.` replaced by `-`. Example: `/home/sergio/Projects/personal/capy` → `-home-sergio-Projects-personal-capy`.\n\nThe mangling function: `strings.NewReplacer(\"/\", \"-\", \".\", \"-\").Replace(absProjectDir)`\n\nThis is based on observed behavior, not official documentation. The implementation should fail gracefully if the derived directory does not exist (log warning, skip session indexing).\n\n### Labels: Machine-Agnostic\n\nLabels use the format `session:<ISO-datetime>:<session-UUID>`. Example:\n```\nsession:2026-04-05T12:06:26Z:102ad512-759a-43ad-8805-353ce341f65c\n```\n\n- **Datetime** comes from the first user message timestamp in the JSONL.\n- **UUID** is the session filename (minus `.jsonl` extension).\n- Datetime-first enables chronological sorting via `source: \"session:\"` filter.\n- UUID ensures uniqueness across machines.\n- No file paths in labels — the knowledge.db remains portable across machines and OS.\n\n### Sweep Algorithm\n\nRuns once per server boot in a background goroutine with 30s timeout:\n\n1. Derive session directory from `projectDir` via path mangling.\n2. List all `.jsonl` files.\n3. Query existing `session:` sources from the store, build `uuid → indexed_at` map (extract UUID by splitting label on `:`).\n4. For each file: compare `max(file.mtime, subagents_dir.mtime)` against `indexed_at`. Skip if mtime <= indexed_at.\n5. Parse JSONL, apply filtering, build transcript, apply session-level gate.\n6. For sessions with `<uuid>/subagents/` directory: parse sub-agent JSONL files, read `meta.json`, append to parent transcript.\n7. Compute content_hash of filtered transcript.\n8. Call `Index()` with label, content type `\"session\"`, kind `KindSession`.\n9. Existing content_hash dedup handles unchanged-but-touched files.\n\nError handling: individual parse failures are logged and skipped. One corrupt file does not block the sweep.\n\n## Session File Format\n\nClaude Code JSONL files contain one JSON object per line. Each has a `type` field. The complete taxonomy (from analysis of 96 sessions across 2 active projects):\n\n### Message Types\n\n| Type | Keep/Skip | Reason |\n|------|-----------|--------|\n| `user` (string content) | **KEEP** | Direct human input |\n| `user` (text blocks in array) | **KEEP** | Human text; strip `<system-reminder>` tags |\n| `user` (tool_result blocks only) | **SKIP** | Automatic SDK returns, no human content |\n| `assistant` text blocks | **KEEP** | Core conversational content |\n| `assistant` thinking blocks | **SKIP** | Content stripped by Claude Code, only base64 signature remains |\n| `assistant` tool_use blocks | **EXTRACT name** | Tool names go in chunk title for BM25 boost |\n| `system/away_summary` | **KEEP** | Dense session recap, high signal |\n| `system/turn_duration` | **SKIP** | Timing metadata |\n| `system/local_command` | **SKIP** | Slash command stdout |\n| `attachment` (all 13 subtypes) | **SKIP** | Infrastructure metadata |\n| `file-history-snapshot` | **SKIP** | File backup metadata |\n| `permission-mode` | **SKIP** | Startup metadata |\n| `progress` | **SKIP** | Progress indicators |\n| `queue-operation` | **SKIP** | Queue metadata |\n| `custom-title` | **SKIP** | Session label |\n| `agent-name` | **SKIP** | Session label |\n| `last-prompt` | **SKIP** | UI state |\n\n### Content Block Types\n\n**User messages:**\n- `message.content` is either a string (19% of messages) or an array (80%).\n- Array blocks: `tool_result` (skip), `text` (keep — but check for `<system-reminder>` tags).\n- `toolUseResult` top-level field: structured tool output annotation. Always skip.\n\n**Assistant messages:**\n- `message.content` is always an array.\n- Block types: `text` (keep), `tool_use` (extract `name` field only), `thinking` (skip — content is empty string, only `signature` field has data).\n- Tool name path: `message.content[i].name` where `message.content[i].type == \"tool_use\"`.\n- Exactly 1 `tool_use` per assistant message (observed invariant).\n\n### Sub-Agent Conversations\n\nSessions that spawned sub-agents have a bare directory `<uuid>/` alongside the `.jsonl` file, containing:\n- `subagents/agent-<hex-id>.jsonl` — full conversation transcript (same JSONL schema, `isSidechain: true`).\n- `subagents/agent-<hex-id>.meta.json` — `{\"agentType\": \"Explore\", \"description\": \"...\"}`.\n- `tool-results/toolu_<id>.json` — offloaded large tool results (rare). Skip these.\n\nSub-agent conversations are parsed and appended to the parent transcript with delimiters:\n```\n--- Subagent: Explore — \"Explore setup command implementation\" ---\nHuman: ...\nAssistant: ...\n--- End subagent ---\n```\n\n## Filtering\n\n### Per-Message Filtering\n\n1. **Skip** user messages where all content blocks are `tool_result` (no `text` blocks).\n2. **Skip** user messages starting with `/` (slash commands — defensive, not observed in stored JSONL).\n3. **Strip** `<system-reminder>...</system-reminder>` tags from text content.\n4. **Skip** `thinking` blocks entirely (content is stripped/empty).\n5. **Extract** tool `name` from `tool_use` blocks for metadata; do not include block content.\n6. **Keep** `system/away_summary` content as inline session summaries.\n7. **Skip** all other non-user/non-assistant types.\n\n### Session-Level Gate\n\nAfter filtering, a session must pass:\n- **Minimum 2 meaningful turn pairs** (human text + assistant text response).\n- **Minimum 200 characters of total assistant text**.\n\nSessions that fail are skipped entirely. Based on analysis: 46% of sessions (44/96) would be filtered out — config-only sessions, aborted conversations, tool-only interactions.\n\n## Chunking\n\n### Transcript Format\n\nFiltered messages are converted to plaintext transcript:\n\n```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]"},"caller":{"type":"direct"}}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":427,"cache_read_input_tokens":124453,"output_tokens":2376,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":427,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGNe5832q5nkLj1djL1","type":"assistant","uuid":"d95ece34-e2bb-482e-9514-e431b2ba959b","timestamp":"2026-04-23T19:37:41.894Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"d95ece34-e2bb-482e-9514-e431b2ba959b","isSidechain":false,"promptId":"8f32cf08-e37b-4a9f-bf36-dbb9fa1721c8","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XwMKhUTS3RMbAucujPkYMY","type":"tool_result","content":"File created successfully at: /home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md"}]},"uuid":"79683c36-436f-4241-a671-c2b218b1fe68","timestamp":"2026-04-23T19:38:15.180Z","toolUseResult":{"type":"create","filePath":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","content":"# Sessionflow RAG — Design Document\n\n> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n> **Status:** Draft\n> **Created:** 2026-04-23\n\n## Problem\n\nClaude Code stores conversation sessions as JSONL files in `~/.claude/projects/<project-dir-name>/`. These sessions contain valuable decisions, rationale, and context that is lost after conversations end. capy already solves context flooding and provides persistent queryable memory, but only for content explicitly indexed during a session — the conversations themselves are invisible to future searches.\n\n## Solution\n\nSessionflow RAG makes past sessions automatically searchable by indexing their human/assistant text content into capy's FTS5 knowledge base. A background sweep runs at MCP server startup, parsing session JSONL files, filtering out noise, chunking the conversational text into BM25-friendly windows, and indexing them under a new `KindSession` source kind.\n\nThe feature is entirely automatic — no MCP tool is exposed, the assistant never needs to think about it, and the indexed content stays portable across machines by using machine-agnostic labels (session UUID + datetime, not file paths).\n\n## Design Decisions\n\n### Source Kind: `KindSession`\n\nA new source kind alongside `KindDurable` and `KindEphemeral`. Sessions have a distinct lifecycle: they are not transient command output (ephemeral) nor explicitly curated knowledge (durable). They represent conversational history with a natural decay curve measured in weeks/months.\n\n- **Cleanup:** Strict TTL (default 60 days, configurable via `session_ttl_days`), same mechanism as ephemeral. Access count is ignored — sessions decay by age, not usage frequency.\n- **Search:** Included in default search results alongside durable content. Users can exclude via `include_kinds: [\"durable\"]`.\n- **Stats:** Reported separately with fresh/stale TTL bucketing.\n\n### Indexing Trigger: MCP Server Startup\n\nIndexing runs as a background goroutine fired during `Server.Serve()`. This was chosen over alternatives:\n\n- **Session-end hook** — rejected. The hook is a short-lived process; goroutines die when it exits. Also risks DB lock contention with the dying MCP server (see `internal/hook/sessionend.go` WAL warning).\n- **Session-start hook** — rejected for the same lifecycle reason (short-lived process).\n- **MCP server startup** — chosen. The server is a long-lived process with safe DB access. A background goroutine doesn't block Claude Code's UI. The 1-2 second delay before the previous session becomes searchable is invisible.\n\nTrade-off: one-session delay before content is searchable. Acceptable because you never search the current session.\n\n### Session Directory Discovery\n\nClaude Code stores sessions in `~/.claude/projects/<dir-name>/` where `<dir-name>` is the absolute project path with `/` and `.` replaced by `-`. Example: `/home/sergio/Projects/personal/capy` → `-home-sergio-Projects-personal-capy`.\n\nThe mangling function: `strings.NewReplacer(\"/\", \"-\", \".\", \"-\").Replace(absProjectDir)`\n\nThis is based on observed behavior, not official documentation. The implementation should fail gracefully if the derived directory does not exist (log warning, skip session indexing).\n\n### Labels: Machine-Agnostic\n\nLabels use the format `session:<ISO-datetime>:<session-UUID>`. Example:\n```\nsession:2026-04-05T12:06:26Z:102ad512-759a-43ad-8805-353ce341f65c\n```\n\n- **Datetime** comes from the first user message timestamp in the JSONL.\n- **UUID** is the session filename (minus `.jsonl` extension).\n- Datetime-first enables chronological sorting via `source: \"session:\"` filter.\n- UUID ensures uniqueness across machines.\n- No file paths in labels — the knowledge.db remains portable across machines and OS.\n\n### Sweep Algorithm\n\nRuns once per server boot in a background goroutine with 30s timeout:\n\n1. Derive session directory from `projectDir` via path mangling.\n2. List all `.jsonl` files.\n3. Query existing `session:` sources from the store, build `uuid → indexed_at` map (extract UUID by splitting label on `:`).\n4. For each file: compare `max(file.mtime, subagents_dir.mtime)` against `indexed_at`. Skip if mtime <= indexed_at.\n5. Parse JSONL, apply filtering, build transcript, apply session-level gate.\n6. For sessions with `<uuid>/subagents/` directory: parse sub-agent JSONL files, read `meta.json`, append to parent transcript.\n7. Compute content_hash of filtered transcript.\n8. Call `Index()` with label, content type `\"session\"`, kind `KindSession`.\n9. Existing content_hash dedup handles unchanged-but-touched files.\n\nError handling: individual parse failures are logged and skipped. One corrupt file does not block the sweep.\n\n## Session File Format\n\nClaude Code JSONL files contain one JSON object per line. Each has a `type` field. The complete taxonomy (from analysis of 96 sessions across 2 active projects):\n\n### Message Types\n\n| Type | Keep/Skip | Reason |\n|------|-----------|--------|\n| `user` (string content) | **KEEP** | Direct human input |\n| `user` (text blocks in array) | **KEEP** | Human text; strip `<system-reminder>` tags |\n| `user` (tool_result blocks only) | **SKIP** | Automatic SDK returns, no human content |\n| `assistant` text blocks | **KEEP** | Core conversational content |\n| `assistant` thinking blocks | **SKIP** | Content stripped by Claude Code, only base64 signature remains |\n| `assistant` tool_use blocks | **EXTRACT name** | Tool names go in chunk title for BM25 boost |\n| `system/away_summary` | **KEEP** | Dense session recap, high signal |\n| `system/turn_duration` | **SKIP** | Timing metadata |\n| `system/local_command` | **SKIP** | Slash command stdout |\n| `attachment` (all 13 subtypes) | **SKIP** | Infrastructure metadata |\n| `file-history-snapshot` | **SKIP** | File backup metadata |\n| `permission-mode` | **SKIP** | Startup metadata |\n| `progress` | **SKIP** | Progress indicators |\n| `queue-operation` | **SKIP** | Queue metadata |\n| `custom-title` | **SKIP** | Session label |\n| `agent-name` | **SKIP** | Session label |\n| `last-prompt` | **SKIP** | UI state |\n\n### Content Block Types\n\n**User messages:**\n- `message.content` is either a string (19% of messages) or an array (80%).\n- Array blocks: `tool_result` (skip), `text` (keep — but check for `<system-reminder>` tags).\n- `toolUseResult` top-level field: structured tool output annotation. Always skip.\n\n**Assistant messages:**\n- `message.content` is always an array.\n- Block types: `text` (keep), `tool_use` (extract `name` field only), `thinking` (skip — content is empty string, only `signature` field has data).\n- Tool name path: `message.content[i].name` where `message.content[i].type == \"tool_use\"`.\n- Exactly 1 `tool_use` per assistant message (observed invariant).\n\n### Sub-Agent Conversations\n\nSessions that spawned sub-agents have a bare directory `<uuid>/` alongside the `.jsonl` file, containing:\n- `subagents/agent-<hex-id>.jsonl` — full conversation transcript (same JSONL schema, `isSidechain: true`).\n- `subagents/agent-<hex-id>.meta.json` — `{\"agentType\": \"Explore\", \"description\": \"...\"}`.\n- `tool-results/toolu_<id>.json` — offloaded large tool results (rare). Skip these.\n\nSub-agent conversations are parsed and appended to the parent transcript with delimiters:\n```\n--- Subagent: Explore — \"Explore setup command implementation\" ---\nHuman: ...\nAssistant: ...\n--- End subagent ---\n```\n\n## Filtering\n\n### Per-Message Filtering\n\n1. **Skip** user messages where all content blocks are `tool_result` (no `text` blocks).\n2. **Skip** user messages starting with `/` (slash commands — defensive, not observed in stored JSONL).\n3. **Strip** `<system-reminder>...</system-reminder>` tags from text content.\n4. **Skip** `thinking` blocks entirely (content is stripped/empty).\n5. **Extract** tool `name` from `tool_use` blocks for metadata; do not include block content.\n6. **Keep** `system/away_summary` content as inline session summaries.\n7. **Skip** all other non-user/non-assistant types.\n\n### Session-Level Gate\n\nAfter filtering, a session must pass:\n- **Minimum 2 meaningful turn pairs** (human text + assistant text response).\n- **Minimum 200 characters of total assistant text**.\n\nSessions that fail are skipped entirely. Based on analysis: 46% of sessions (44/96) would be filtered out — config-only sessions, aborted conversations, tool-only interactions.\n\n## Chunking\n\n### Transcript Format\n\nFiltered messages are converted to plaintext transcript:\n\n```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]","structuredPatch":[],"originalFile":null,"userModified":false},"sourceToolAssistantUUID":"d95ece34-e2bb-482e-9514-e431b2ba959b","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"last-prompt","lastPrompt":"Proceed to next step","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
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 {"parentUuid":"982cb2f0-20af-45d3-9cd3-d873ce1604b7","isSidechain":false,"promptId":"8f32cf08-e37b-4a9f-bf36-dbb9fa1721c8","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CPehie6QMf3MnpjXkQqDn2","type":"tool_result","content":"1\t# Sessionflow RAG — Design Document\n2\t\n3\t> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n4\t> **Status:** Draft\n5\t> **Created:** 2026-04-23"}]},"uuid":"c55e5ba3-c78a-4c5f-baf9-2d599cfd00f5","timestamp":"2026-04-23T19:38:18.178Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","content":"# Sessionflow RAG — Design Document\n\n> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n> **Status:** Draft\n> **Created:** 2026-04-23","numLines":5,"startLine":1,"totalLines":157}},"sourceToolAssistantUUID":"982cb2f0-20af-45d3-9cd3-d873ce1604b7","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"c55e5ba3-c78a-4c5f-baf9-2d599cfd00f5","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_0145JUnDWqECMtHNAXZq7Aip","type":"message","role":"assistant","content":[{"type":"text","text":"The file was truncated during write. Let me complete it and write the full design doc properly."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":2626,"cache_read_input_tokens":124880,"output_tokens":116,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":2626,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGWBNEmf6LQ1zumi47q","type":"assistant","uuid":"dbe2eebe-5e04-41dd-975c-82b38464880e","timestamp":"2026-04-23T19:38:21.130Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"a2c0f037-f163-421a-a492-18f60f25788e","isSidechain":false,"promptId":"8f32cf08-e37b-4a9f-bf36-dbb9fa1721c8","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01U3z4yycyY8GGx9NRtKiBKz","type":"tool_result","content":"<system-reminder>Warning: the file exists but is shorter than the provided offset (190). The file has 157 lines.</system-reminder>"}]},"uuid":"c16beab9-400d-43ac-a7ab-15ecd28b8bcc","timestamp":"2026-04-23T19:38:21.735Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","content":"","numLines":0,"startLine":190,"totalLines":157}},"sourceToolAssistantUUID":"a2c0f037-f163-421a-a492-18f60f25788e","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"c16beab9-400d-43ac-a7ab-15ecd28b8bcc","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_017yUvb4CEbF8smpzQjN6j1P","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JYTzF5rv6aa8VinaMD7wVV","name":"Read","input":{"file_path":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","offset":145},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":158,"cache_read_input_tokens":127506,"output_tokens":95,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":158,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGWSWZhX1Utgqo8rG1j","type":"assistant","uuid":"266977ea-1528-437b-9248-5129a8e11c47","timestamp":"2026-04-23T19:38:25.440Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"266977ea-1528-437b-9248-5129a8e11c47","isSidechain":false,"promptId":"8f32cf08-e37b-4a9f-bf36-dbb9fa1721c8","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JYTzF5rv6aa8VinaMD7wVV","type":"tool_result","content":"145\t\n146\tSessions that fail are skipped entirely. Based on analysis: 46% of sessions (44/96) would be filtered out — config-only sessions, aborted conversations, tool-only interactions.\n147\t\n148\t## Chunking\n149\t\n150\t### Transcript Format\n151\t\n152\tFiltered messages are converted to plaintext transcript:\n153\t\n154\t```\n155\tHuman: <user text>\n156\tAssistant: <assistant text>\n157\t[Tools: Read, Edit, mcp__capy__capy_search]"}]},"uuid":"2db2b9d2-af5e-4ced-9515-94fc867ecb4b","timestamp":"2026-04-23T19:38:25.469Z","toolUseResult":{"type":"text","file":{"filePath":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","content":"\nSessions that fail are skipped entirely. Based on analysis: 46% of sessions (44/96) would be filtered out — config-only sessions, aborted conversations, tool-only interactions.\n\n## Chunking\n\n### Transcript Format\n\nFiltered messages are converted to plaintext transcript:\n\n```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]","numLines":13,"startLine":145,"totalLines":157}},"sourceToolAssistantUUID":"266977ea-1528-437b-9248-5129a8e11c47","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"2db2b9d2-af5e-4ced-9515-94fc867ecb4b","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Vhc7o9adus7tzDXFHCYM48","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01ATaaRtGHLvL3SD3dVHJzmP","name":"Edit","input":{"replace_all":false,"file_path":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","old_string":"```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]","new_string":"```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]\n\n[Session summary: <away_summary text>]\n\n--- Subagent: Explore — \"Explore setup command implementation\" ---\nHuman: <subagent user text>\nAssistant: <subagent assistant text>\n--- End subagent ---\n```\n\nTool-result-only user messages are omitted from the transcript entirely. The `[Tools: ...]` line appears only when the assistant message contained `tool_use` blocks. Tool names are kept as-is (no normalization of MCP tool names).\n\n### Sliding Window\n\nChunking uses a sliding window of ~4 turn pairs with 1-pair overlap, adapted from `chunkPlainText` in `internal/store/chunk.go`. The split happens on turn boundaries (the `Human:` prefix), not arbitrary line counts.\n\n- **Window size:** ~4 turn pairs. Preserves enough conversational context for BM25 to match multi-turn decisions.\n- **Overlap:** 1 turn pair. If a decision spans two chunks, the overlapping turn appears in both.\n- **Oversized chunks:** Split at paragraph boundaries using existing `splitOversized` logic when exceeding `maxChunkBytes` (4096).\n\n### Chunk Titles\n\nFormat: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Tools: Read, Edit`\n\nWhen the window contains sub-agent turns: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Subagent: Explore | Tools: Read, Edit`\n\nThe title exploits the BM25 title-weight boost in `internal/store/search.go` for targeted retrieval.\n\n### Content Type\n\nChunks use content type `\"session\"` — a new value added to the taxonomy alongside `\"code\"`, `\"prose\"`, `\"plaintext\"`, `\"markdown\"`, `\"json\"`.\n\n## Storage\n\n### Schema Migration\n\nThe `sources` table CHECK constraint changes:\n```sql\n-- Before\nCHECK (kind IN ('ephemeral', 'durable'))\n-- After\nCHECK (kind IN ('ephemeral', 'durable', 'session'))\n```\n\nAdded via `applyMigrations` in `internal/store/migrate.go`, following the existing migration pattern.\n\n### Types\n\n- `KindSession SourceKind = \"session\"` added to `internal/store/types.go`.\n- `Valid()` updated to accept `KindSession`.\n- `\"session\"` added as a content type value.\n\n### Cleanup\n\nSessions use strict TTL, same mechanism as ephemeral. `cleanupEphemeral` is generalized to `cleanupByTTL(kind SourceKind, ttl time.Duration)` and called twice from `Cleanup()`: once for ephemeral (24h), once for session (60 days).\n\n### Config\n\n`CleanupConfig` gains:\n```go\nSessionTTLDays int `toml:\"session_ttl_days\"` // default: 60, minimum: 1\n```\n\n### Search\n\nDefault `IncludeKinds` changes from `[KindDurable]` to `[KindDurable, KindSession]`. The existing `WHERE kind IN (...)` SQL clause supports this.\n\n### Stats\n\n`StoreStats` gains:\n```go\nSessionSourceCount int\nSessionFreshCount  int\nSessionStaleCount  int\n```\n\n`ClassifySources` handles `KindSession` with fresh/stale bucketing using the session TTL.\n\n### CLI Cleanup\n\n- **MCP tool (`capy_cleanup`):** gains `purge_session` boolean flag (mirrors `purge_ephemeral`).\n- **CLI (`capy cleanup`):** gains `--kind` flag for kind-specific cleanup (`capy cleanup --kind session`).\n\n## Integration Points\n\n| Component | Change |\n|-----------|--------|\n| `internal/store/types.go` | `KindSession`, `Valid()`, content type |\n| `internal/store/schema.go` | CHECK constraint (via migration) |\n| `internal/store/migrate.go` | New migration for `session` kind |\n| `internal/store/cleanup.go` | Generalize `cleanupEphemeral` → `cleanupByTTL`, add session cleanup path |\n| `internal/store/chunk.go` | New `chunkTranscript` function |\n| `internal/store/index.go` | Handle `\"session\"` content type routing to `chunkTranscript` |\n| `internal/store/types.go` | `StoreStats` session counters |\n| `internal/config/config.go` | `SessionTTLDays` in `CleanupConfig` |\n| `internal/config/loader.go` | Validation for `SessionTTLDays` |\n| `internal/server/server.go` | Background goroutine for session sweep |\n| `internal/server/tool_cleanup.go` | `purge_session` parameter |\n| `internal/server/tool_stats.go` | Session stats rendering |\n| `internal/server/tool_search.go` | Default `IncludeKinds` update |\n| `cmd/capy/cleanup.go` | `--kind` CLI flag |\n\nNew files:\n| File | Purpose |\n|------|---------|\n| `internal/session/parse.go` | JSONL parsing, message filtering, transcript building |\n| `internal/session/sweep.go` | Session directory discovery, mtime gate, sweep orchestration |\n| `internal/session/parse_test.go` | Unit tests for parsing and filtering |\n| `internal/session/sweep_test.go` | Unit tests for sweep mechanism |\n\n## Open Questions\n\nNone — all design decisions have been made. See the PAL consultation thread for the full decision log including alternatives considered.\n\n## References\n\n- [ADR-017: Source kind separation](../../adr/017-source-kind-separation.md) — establishes the `kind` column and `IncludeKinds` array design\n- [ADR-011: Conservative cleanup policy](../../adr/011-conservative-cleanup-policy.md) — retention scoring (not used for sessions)\n- [GitHub issue #24](https://github.com/serpro69/capy/issues/24) — original feature request\n- Claude Code session format: JSONL in `~/.claude/projects/<dir-name>/`, analyzed from 96 sessions across 2 projects"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":235,"cache_read_input_tokens":127664,"output_tokens":1697,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":235,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGWiPYfxD9j1ajEQdHE","type":"assistant","uuid":"7381b0ff-da11-4c4c-a738-025b4b227af5","timestamp":"2026-04-23T19:38:57.644Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"7381b0ff-da11-4c4c-a738-025b4b227af5","isSidechain":false,"promptId":"8f32cf08-e37b-4a9f-bf36-dbb9fa1721c8","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01ATaaRtGHLvL3SD3dVHJzmP","type":"tool_result","content":"The file /home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md has been updated successfully."}]},"uuid":"d85353c9-8d02-4a37-8feb-575117bbd72e","timestamp":"2026-04-23T19:38:57.758Z","toolUseResult":{"filePath":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/design.md","oldString":"```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]","newString":"```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]\n\n[Session summary: <away_summary text>]\n\n--- Subagent: Explore — \"Explore setup command implementation\" ---\nHuman: <subagent user text>\nAssistant: <subagent assistant text>\n--- End subagent ---\n```\n\nTool-result-only user messages are omitted from the transcript entirely. The `[Tools: ...]` line appears only when the assistant message contained `tool_use` blocks. Tool names are kept as-is (no normalization of MCP tool names).\n\n### Sliding Window\n\nChunking uses a sliding window of ~4 turn pairs with 1-pair overlap, adapted from `chunkPlainText` in `internal/store/chunk.go`. The split happens on turn boundaries (the `Human:` prefix), not arbitrary line counts.\n\n- **Window size:** ~4 turn pairs. Preserves enough conversational context for BM25 to match multi-turn decisions.\n- **Overlap:** 1 turn pair. If a decision spans two chunks, the overlapping turn appears in both.\n- **Oversized chunks:** Split at paragraph boundaries using existing `splitOversized` logic when exceeding `maxChunkBytes` (4096).\n\n### Chunk Titles\n\nFormat: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Tools: Read, Edit`\n\nWhen the window contains sub-agent turns: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Subagent: Explore | Tools: Read, Edit`\n\nThe title exploits the BM25 title-weight boost in `internal/store/search.go` for targeted retrieval.\n\n### Content Type\n\nChunks use content type `\"session\"` — a new value added to the taxonomy alongside `\"code\"`, `\"prose\"`, `\"plaintext\"`, `\"markdown\"`, `\"json\"`.\n\n## Storage\n\n### Schema Migration\n\nThe `sources` table CHECK constraint changes:\n```sql\n-- Before\nCHECK (kind IN ('ephemeral', 'durable'))\n-- After\nCHECK (kind IN ('ephemeral', 'durable', 'session'))\n```\n\nAdded via `applyMigrations` in `internal/store/migrate.go`, following the existing migration pattern.\n\n### Types\n\n- `KindSession SourceKind = \"session\"` added to `internal/store/types.go`.\n- `Valid()` updated to accept `KindSession`.\n- `\"session\"` added as a content type value.\n\n### Cleanup\n\nSessions use strict TTL, same mechanism as ephemeral. `cleanupEphemeral` is generalized to `cleanupByTTL(kind SourceKind, ttl time.Duration)` and called twice from `Cleanup()`: once for ephemeral (24h), once for session (60 days).\n\n### Config\n\n`CleanupConfig` gains:\n```go\nSessionTTLDays int `toml:\"session_ttl_days\"` // default: 60, minimum: 1\n```\n\n### Search\n\nDefault `IncludeKinds` changes from `[KindDurable]` to `[KindDurable, KindSession]`. The existing `WHERE kind IN (...)` SQL clause supports this.\n\n### Stats\n\n`StoreStats` gains:\n```go\nSessionSourceCount int\nSessionFreshCount  int\nSessionStaleCount  int\n```\n\n`ClassifySources` handles `KindSession` with fresh/stale bucketing using the session TTL.\n\n### CLI Cleanup\n\n- **MCP tool (`capy_cleanup`):** gains `purge_session` boolean flag (mirrors `purge_ephemeral`).\n- **CLI (`capy cleanup`):** gains `--kind` flag for kind-specific cleanup (`capy cleanup --kind session`).\n\n## Integration Points\n\n| Component | Change |\n|-----------|--------|\n| `internal/store/types.go` | `KindSession`, `Valid()`, content type |\n| `internal/store/schema.go` | CHECK constraint (via migration) |\n| `internal/store/migrate.go` | New migration for `session` kind |\n| `internal/store/cleanup.go` | Generalize `cleanupEphemeral` → `cleanupByTTL`, add session cleanup path |\n| `internal/store/chunk.go` | New `chunkTranscript` function |\n| `internal/store/index.go` | Handle `\"session\"` content type routing to `chunkTranscript` |\n| `internal/store/types.go` | `StoreStats` session counters |\n| `internal/config/config.go` | `SessionTTLDays` in `CleanupConfig` |\n| `internal/config/loader.go` | Validation for `SessionTTLDays` |\n| `internal/server/server.go` | Background goroutine for session sweep |\n| `internal/server/tool_cleanup.go` | `purge_session` parameter |\n| `internal/server/tool_stats.go` | Session stats rendering |\n| `internal/server/tool_search.go` | Default `IncludeKinds` update |\n| `cmd/capy/cleanup.go` | `--kind` CLI flag |\n\nNew files:\n| File | Purpose |\n|------|---------|\n| `internal/session/parse.go` | JSONL parsing, message filtering, transcript building |\n| `internal/session/sweep.go` | Session directory discovery, mtime gate, sweep orchestration |\n| `internal/session/parse_test.go` | Unit tests for parsing and filtering |\n| `internal/session/sweep_test.go` | Unit tests for sweep mechanism |\n\n## Open Questions\n\nNone — all design decisions have been made. See the PAL consultation thread for the full decision log including alternatives considered.\n\n## References\n\n- [ADR-017: Source kind separation](../../adr/017-source-kind-separation.md) — establishes the `kind` column and `IncludeKinds` array design\n- [ADR-011: Conservative cleanup policy](../../adr/011-conservative-cleanup-policy.md) — retention scoring (not used for sessions)\n- [GitHub issue #24](https://github.com/serpro69/capy/issues/24) — original feature request\n- Claude Code session format: JSONL in `~/.claude/projects/<dir-name>/`, analyzed from 96 sessions across 2 projects","originalFile":"# Sessionflow RAG — Design Document\n\n> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n> **Status:** Draft\n> **Created:** 2026-04-23\n\n## Problem\n\nClaude Code stores conversation sessions as JSONL files in `~/.claude/projects/<project-dir-name>/`. These sessions contain valuable decisions, rationale, and context that is lost after conversations end. capy already solves context flooding and provides persistent queryable memory, but only for content explicitly indexed during a session — the conversations themselves are invisible to future searches.\n\n## Solution\n\nSessionflow RAG makes past sessions automatically searchable by indexing their human/assistant text content into capy's FTS5 knowledge base. A background sweep runs at MCP server startup, parsing session JSONL files, filtering out noise, chunking the conversational text into BM25-friendly windows, and indexing them under a new `KindSession` source kind.\n\nThe feature is entirely automatic — no MCP tool is exposed, the assistant never needs to think about it, and the indexed content stays portable across machines by using machine-agnostic labels (session UUID + datetime, not file paths).\n\n## Design Decisions\n\n### Source Kind: `KindSession`\n\nA new source kind alongside `KindDurable` and `KindEphemeral`. Sessions have a distinct lifecycle: they are not transient command output (ephemeral) nor explicitly curated knowledge (durable). They represent conversational history with a natural decay curve measured in weeks/months.\n\n- **Cleanup:** Strict TTL (default 60 days, configurable via `session_ttl_days`), same mechanism as ephemeral. Access count is ignored — sessions decay by age, not usage frequency.\n- **Search:** Included in default search results alongside durable content. Users can exclude via `include_kinds: [\"durable\"]`.\n- **Stats:** Reported separately with fresh/stale TTL bucketing.\n\n### Indexing Trigger: MCP Server Startup\n\nIndexing runs as a background goroutine fired during `Server.Serve()`. This was chosen over alternatives:\n\n- **Session-end hook** — rejected. The hook is a short-lived process; goroutines die when it exits. Also risks DB lock contention with the dying MCP server (see `internal/hook/sessionend.go` WAL warning).\n- **Session-start hook** — rejected for the same lifecycle reason (short-lived process).\n- **MCP server startup** — chosen. The server is a long-lived process with safe DB access. A background goroutine doesn't block Claude Code's UI. The 1-2 second delay before the previous session becomes searchable is invisible.\n\nTrade-off: one-session delay before content is searchable. Acceptable because you never search the current session.\n\n### Session Directory Discovery\n\nClaude Code stores sessions in `~/.claude/projects/<dir-name>/` where `<dir-name>` is the absolute project path with `/` and `.` replaced by `-`. Example: `/home/sergio/Projects/personal/capy` → `-home-sergio-Projects-personal-capy`.\n\nThe mangling function: `strings.NewReplacer(\"/\", \"-\", \".\", \"-\").Replace(absProjectDir)`\n\nThis is based on observed behavior, not official documentation. The implementation should fail gracefully if the derived directory does not exist (log warning, skip session indexing).\n\n### Labels: Machine-Agnostic\n\nLabels use the format `session:<ISO-datetime>:<session-UUID>`. Example:\n```\nsession:2026-04-05T12:06:26Z:102ad512-759a-43ad-8805-353ce341f65c\n```\n\n- **Datetime** comes from the first user message timestamp in the JSONL.\n- **UUID** is the session filename (minus `.jsonl` extension).\n- Datetime-first enables chronological sorting via `source: \"session:\"` filter.\n- UUID ensures uniqueness across machines.\n- No file paths in labels — the knowledge.db remains portable across machines and OS.\n\n### Sweep Algorithm\n\nRuns once per server boot in a background goroutine with 30s timeout:\n\n1. Derive session directory from `projectDir` via path mangling.\n2. List all `.jsonl` files.\n3. Query existing `session:` sources from the store, build `uuid → indexed_at` map (extract UUID by splitting label on `:`).\n4. For each file: compare `max(file.mtime, subagents_dir.mtime)` against `indexed_at`. Skip if mtime <= indexed_at.\n5. Parse JSONL, apply filtering, build transcript, apply session-level gate.\n6. For sessions with `<uuid>/subagents/` directory: parse sub-agent JSONL files, read `meta.json`, append to parent transcript.\n7. Compute content_hash of filtered transcript.\n8. Call `Index()` with label, content type `\"session\"`, kind `KindSession`.\n9. Existing content_hash dedup handles unchanged-but-touched files.\n\nError handling: individual parse failures are logged and skipped. One corrupt file does not block the sweep.\n\n## Session File Format\n\nClaude Code JSONL files contain one JSON object per line. Each has a `type` field. The complete taxonomy (from analysis of 96 sessions across 2 active projects):\n\n### Message Types\n\n| Type | Keep/Skip | Reason |\n|------|-----------|--------|\n| `user` (string content) | **KEEP** | Direct human input |\n| `user` (text blocks in array) | **KEEP** | Human text; strip `<system-reminder>` tags |\n| `user` (tool_result blocks only) | **SKIP** | Automatic SDK returns, no human content |\n| `assistant` text blocks | **KEEP** | Core conversational content |\n| `assistant` thinking blocks | **SKIP** | Content stripped by Claude Code, only base64 signature remains |\n| `assistant` tool_use blocks | **EXTRACT name** | Tool names go in chunk title for BM25 boost |\n| `system/away_summary` | **KEEP** | Dense session recap, high signal |\n| `system/turn_duration` | **SKIP** | Timing metadata |\n| `system/local_command` | **SKIP** | Slash command stdout |\n| `attachment` (all 13 subtypes) | **SKIP** | Infrastructure metadata |\n| `file-history-snapshot` | **SKIP** | File backup metadata |\n| `permission-mode` | **SKIP** | Startup metadata |\n| `progress` | **SKIP** | Progress indicators |\n| `queue-operation` | **SKIP** | Queue metadata |\n| `custom-title` | **SKIP** | Session label |\n| `agent-name` | **SKIP** | Session label |\n| `last-prompt` | **SKIP** | UI state |\n\n### Content Block Types\n\n**User messages:**\n- `message.content` is either a string (19% of messages) or an array (80%).\n- Array blocks: `tool_result` (skip), `text` (keep — but check for `<system-reminder>` tags).\n- `toolUseResult` top-level field: structured tool output annotation. Always skip.\n\n**Assistant messages:**\n- `message.content` is always an array.\n- Block types: `text` (keep), `tool_use` (extract `name` field only), `thinking` (skip — content is empty string, only `signature` field has data).\n- Tool name path: `message.content[i].name` where `message.content[i].type == \"tool_use\"`.\n- Exactly 1 `tool_use` per assistant message (observed invariant).\n\n### Sub-Agent Conversations\n\nSessions that spawned sub-agents have a bare directory `<uuid>/` alongside the `.jsonl` file, containing:\n- `subagents/agent-<hex-id>.jsonl` — full conversation transcript (same JSONL schema, `isSidechain: true`).\n- `subagents/agent-<hex-id>.meta.json` — `{\"agentType\": \"Explore\", \"description\": \"...\"}`.\n- `tool-results/toolu_<id>.json` — offloaded large tool results (rare). Skip these.\n\nSub-agent conversations are parsed and appended to the parent transcript with delimiters:\n```\n--- Subagent: Explore — \"Explore setup command implementation\" ---\nHuman: ...\nAssistant: ...\n--- End subagent ---\n```\n\n## Filtering\n\n### Per-Message Filtering\n\n1. **Skip** user messages where all content blocks are `tool_result` (no `text` blocks).\n2. **Skip** user messages starting with `/` (slash commands — defensive, not observed in stored JSONL).\n3. **Strip** `<system-reminder>...</system-reminder>` tags from text content.\n4. **Skip** `thinking` blocks entirely (content is stripped/empty).\n5. **Extract** tool `name` from `tool_use` blocks for metadata; do not include block content.\n6. **Keep** `system/away_summary` content as inline session summaries.\n7. **Skip** all other non-user/non-assistant types.\n\n### Session-Level Gate\n\nAfter filtering, a session must pass:\n- **Minimum 2 meaningful turn pairs** (human text + assistant text response).\n- **Minimum 200 characters of total assistant text**.\n\nSessions that fail are skipped entirely. Based on analysis: 46% of sessions (44/96) would be filtered out — config-only sessions, aborted conversations, tool-only interactions.\n\n## Chunking\n\n### Transcript Format\n\nFiltered messages are converted to plaintext transcript:\n\n```\nHuman: <user text>\nAssistant: <assistant text>\n[Tools: Read, Edit, mcp__capy__capy_search]","structuredPatch":[{"oldStart":154,"oldLines":4,"newStart":154,"newLines":123,"lines":[" ```"," Human: <user text>"," Assistant: <assistant text>","-[Tools: Read, Edit, mcp__capy__capy_search]","\\ No newline at end of file","+[Tools: Read, Edit, mcp__capy__capy_search]","+","+[Session summary: <away_summary text>]","+","+--- Subagent: Explore — \"Explore setup command implementation\" ---","+Human: <subagent user text>","+Assistant: <subagent assistant text>","+--- End subagent ---","+```","+","+Tool-result-only user messages are omitted from the transcript entirely. The `[Tools: ...]` line appears only when the assistant message contained `tool_use` blocks. Tool names are kept as-is (no normalization of MCP tool names).","+","+### Sliding Window","+","+Chunking uses a sliding window of ~4 turn pairs with 1-pair overlap, adapted from `chunkPlainText` in `internal/store/chunk.go`. The split happens on turn boundaries (the `Human:` prefix), not arbitrary line counts.","+","+- **Window size:** ~4 turn pairs. Preserves enough conversational context for BM25 to match multi-turn decisions.","+- **Overlap:** 1 turn pair. If a decision spans two chunks, the overlapping turn appears in both.","+- **Oversized chunks:** Split at paragraph boundaries using existing `splitOversized` logic when exceeding `maxChunkBytes` (4096).","+","+### Chunk Titles","+","+Format: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Tools: Read, Edit`","+","+When the window contains sub-agent turns: `Session 2026-04-05T12:06:26Z | Turns 3-6 | Subagent: Explore | Tools: Read, Edit`","+","+The title exploits the BM25 title-weight boost in `internal/store/search.go` for targeted retrieval.","+","+### Content Type","+","+Chunks use content type `\"session\"` — a new value added to the taxonomy alongside `\"code\"`, `\"prose\"`, `\"plaintext\"`, `\"markdown\"`, `\"json\"`.","+","+## Storage","+","+### Schema Migration","+","+The `sources` table CHECK constraint changes:","+```sql","+-- Before","+CHECK (kind IN ('ephemeral', 'durable'))","+-- After","+CHECK (kind IN ('ephemeral', 'durable', 'session'))","+```","+","+Added via `applyMigrations` in `internal/store/migrate.go`, following the existing migration pattern.","+","+### Types","+","+- `KindSession SourceKind = \"session\"` added to `internal/store/types.go`.","+- `Valid()` updated to accept `KindSession`.","+- `\"session\"` added as a content type value.","+","+### Cleanup","+","+Sessions use strict TTL, same mechanism as ephemeral. `cleanupEphemeral` is generalized to `cleanupByTTL(kind SourceKind, ttl time.Duration)` and called twice from `Cleanup()`: once for ephemeral (24h), once for session (60 days).","+","+### Config","+","+`CleanupConfig` gains:","+```go","+SessionTTLDays int `toml:\"session_ttl_days\"` // default: 60, minimum: 1","+```","+","+### Search","+","+Default `IncludeKinds` changes from `[KindDurable]` to `[KindDurable, KindSession]`. The existing `WHERE kind IN (...)` SQL clause supports this.","+","+### Stats","+","+`StoreStats` gains:","+```go","+SessionSourceCount int","+SessionFreshCount  int","+SessionStaleCount  int","+```","+","+`ClassifySources` handles `KindSession` with fresh/stale bucketing using the session TTL.","+","+### CLI Cleanup","+","+- **MCP tool (`capy_cleanup`):** gains `purge_session` boolean flag (mirrors `purge_ephemeral`).","+- **CLI (`capy cleanup`):** gains `--kind` flag for kind-specific cleanup (`capy cleanup --kind session`).","+","+## Integration Points","+","+| Component | Change |","+|-----------|--------|","+| `internal/store/types.go` | `KindSession`, `Valid()`, content type |","+| `internal/store/schema.go` | CHECK constraint (via migration) |","+| `internal/store/migrate.go` | New migration for `session` kind |","+| `internal/store/cleanup.go` | Generalize `cleanupEphemeral` → `cleanupByTTL`, add session cleanup path |","+| `internal/store/chunk.go` | New `chunkTranscript` function |","+| `internal/store/index.go` | Handle `\"session\"` content type routing to `chunkTranscript` |","+| `internal/store/types.go` | `StoreStats` session counters |","+| `internal/config/config.go` | `SessionTTLDays` in `CleanupConfig` |","+| `internal/config/loader.go` | Validation for `SessionTTLDays` |","+| `internal/server/server.go` | Background goroutine for session sweep |","+| `internal/server/tool_cleanup.go` | `purge_session` parameter |","+| `internal/server/tool_stats.go` | Session stats rendering |","+| `internal/server/tool_search.go` | Default `IncludeKinds` update |","+| `cmd/capy/cleanup.go` | `--kind` CLI flag |","+","+New files:","+| File | Purpose |","+|------|---------|","+| `internal/session/parse.go` | JSONL parsing, message filtering, transcript building |","+| `internal/session/sweep.go` | Session directory discovery, mtime gate, sweep orchestration |","+| `internal/session/parse_test.go` | Unit tests for parsing and filtering |","+| `internal/session/sweep_test.go` | Unit tests for sweep mechanism |","+","+## Open Questions","+","+None — all design decisions have been made. See the PAL consultation thread for the full decision log including alternatives considered.","+","+## References","+","+- [ADR-017: Source kind separation](../../adr/017-source-kind-separation.md) — establishes the `kind` column and `IncludeKinds` array design","+- [ADR-011: Conservative cleanup policy](../../adr/011-conservative-cleanup-policy.md) — retention scoring (not used for sessions)","+- [GitHub issue #24](https://github.com/serpro69/capy/issues/24) — original feature request","+- Claude Code session format: JSONL in `~/.claude/projects/<dir-name>/`, analyzed from 96 sessions across 2 projects","\\ No newline at end of file"]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"7381b0ff-da11-4c4c-a738-025b4b227af5","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"type":"last-prompt","lastPrompt":"Proceed to next step","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"type":"permission-mode","permissionMode":"acceptEdits","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096"}
 {"parentUuid":"d85353c9-8d02-4a37-8feb-575117bbd72e","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01427mKNskGALmobRjiCcBia","type":"message","role":"assistant","content":[{"type":"text","text":"Now the implementation plan."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1760,"cache_read_input_tokens":127899,"output_tokens":3887,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1760,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGZ6wRP9X2JLjekUc4X","type":"assistant","uuid":"0a4f762d-7484-4516-b255-511c4733e8f8","timestamp":"2026-04-23T19:39:00.510Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
 {"parentUuid":"0a4f762d-7484-4516-b255-511c4733e8f8","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01427mKNskGALmobRjiCcBia","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MzGdr5zKkWhwSnBnU2XwcD","name":"Write","input":{"file_path":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/implementation.md","content":"# Sessionflow RAG — Implementation Plan\n\n> **Design:** [./design.md](./design.md)\n> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n> **Created:** 2026-04-23\n\nThis plan is ordered for incremental development. Each task builds on the previous and can be verified independently. The developer should be familiar with Go and SQLite but may have no prior context on the capy codebase.\n\n## Prerequisites\n\nRead these files before starting:\n- `CONTRIBUTING.md` — build instructions, test patterns, project structure\n- `internal/store/types.go` — source kinds, chunk types, search/index result types\n- `internal/store/schema.go` — FTS5 schema\n- `internal/store/index.go` — `Index()` function, content_hash dedup, `chunkContent` routing\n- `internal/store/cleanup.go` — retention scoring, `cleanupEphemeral`, `Cleanup()`\n- `internal/store/chunk.go` — `chunkPlainText`, `chunkMarkdown`, splitting strategies\n- `internal/server/server.go` — `Server` struct, `Serve()`, `getStore()`, `ephemeralTTL()`\n- `internal/config/config.go` — `Config`, `CleanupConfig`, `DefaultConfig()`\n- `docs/adr/017-source-kind-separation.md` — why source kinds exist, the `IncludeKinds` design\n\nAll tests require `-tags fts5`. Use `make test` or `go test -tags fts5 -count=1 ./...`.\n\n---\n\n## Phase 1: Storage Foundation\n\n### 1.1 Add KindSession to types\n\n**File:** `internal/store/types.go`\n\n- Add `KindSession SourceKind = \"session\"` constant.\n- Update `Valid()` to return true for `KindSession`.\n- Add session-specific fields to `StoreStats`: `SessionSourceCount`, `SessionFreshCount`, `SessionStaleCount`.\n\n**Verify:** existing tests still pass (`go test -tags fts5 ./internal/store/...`). No behavioral change yet.\n\n### 1.2 Schema migration\n\n**File:** `internal/store/migrate.go`\n\nAdd a new migration that alters the CHECK constraint on `sources.kind` to accept `'session'`. SQLite does not support `ALTER TABLE ... ALTER CONSTRAINT`, so the migration must:\n\n1. Create a new table with the updated CHECK constraint.\n2. Copy all data from the old table.\n3. Drop the old table.\n4. Rename the new table.\n\nFollow the existing migration pattern in `migrate.go`. The migration number should be the next sequential one.\n\n**Verify:** `go test -tags fts5 ./internal/store/...` — migration applies cleanly. Open a test DB, insert a source with `kind = 'session'`, confirm no constraint violation.\n\n### 1.3 Config: SessionTTLDays\n\n**File:** `internal/config/config.go`\n\n- Add `SessionTTLDays int` to `CleanupConfig` with toml tag `session_ttl_days`.\n- Set default to 60 in `DefaultConfig()`.\n\n**File:** `internal/config/loader.go`\n\n- Add validation: `SessionTTLDays` must be >= 1. Reject with error if < 1.\n\n**File:** `internal/server/server.go`\n\n- Add `sessionTTL()` method mirroring `ephemeralTTL()`: resolves TTL from config with 60-day fallback.\n\n**Verify:** `go test -tags fts5 ./internal/config/...` — config loads with default, rejects invalid values.\n\n### 1.4 Cleanup: Generalize TTL-based eviction\n\n**File:** `internal/store/cleanup.go`\n\n- Rename `cleanupEphemeral` to `cleanupByTTL(kind SourceKind, ttl time.Duration)`. The only change: the `WHERE kind = ?` parameter becomes the `kind` argument instead of hardcoded `KindEphemeral`.\n- Update `Cleanup()` to call `cleanupByTTL` twice: once for `KindEphemeral` with ephemeral TTL, once for `KindSession` with session TTL.\n- Update `PurgeEphemeral` to call `cleanupByTTL(KindEphemeral, ttl)`.\n- Add `PurgeSession(dryRun bool, ttl time.Duration)` that calls `cleanupByTTL(KindSession, ttl)`.\n- Update `ClassifySources` to handle `KindSession` with fresh/stale bucketing using session TTL.\n- Update `Stats()` to accept both TTLs (or a TTL map) and populate session counters.\n\n**Verify:** `go test -tags fts5 ./internal/store/...` — existing ephemeral cleanup tests pass. Add tests for session TTL cleanup: index a session-kind source, advance clock past TTL, verify eviction.\n\n### 1.5 Search: Update default IncludeKinds\n\n**File:** `internal/server/tool_search.go`\n\n- Update the default `IncludeKinds` from `[KindDurable]` to `[KindDurable, KindSession]`.\n\n**File:** `internal/server/intent_search.go` (if applicable)\n\n- Verify intent search does not need session kind changes (it writes ephemeral, searches durable).\n\n**Verify:** index a session-kind source manually, search for its content, verify it appears in results. Verify ephemeral sources are still excluded by default.\n\n---\n\n## Phase 2: Session Parsing\n\n### 2.1 JSONL parser\n\n**New file:** `internal/session/parse.go`\n\nCreate a session JSONL parser that reads a file and produces a filtered transcript. The parser:\n\n1. Reads the file line by line.\n2. Parses each line as JSON.\n3. Routes on `type` field:\n   - `\"user\"`: extract text content (string or text blocks from array). Skip tool_result-only messages. Skip messages starting with `/`. Strip `<system-reminder>` tags.\n   - `\"assistant\"`: extract text from `text` blocks. Extract tool names from `tool_use` blocks. Skip `thinking` blocks.\n   - `\"system\"` with `subtype == \"away_summary\"`: extract `content` field.\n   - All other types: skip.\n4. Builds turn pairs: a turn pair is a human text message followed by assistant text response(s). Tool names from assistant tool_use blocks are collected per turn.\n5. Extracts session metadata: first user message timestamp (for the label datetime), session UUID (from `sessionId` field or filename).\n\n**Output type:**\n\n```go\ntype ParsedSession struct {\n    SessionID  string\n    StartTime  time.Time\n    TurnPairs  []TurnPair\n    TotalAssistantChars int\n}\n\ntype TurnPair struct {\n    HumanText     string\n    AssistantText string\n    ToolNames     []string\n    IsSubagent    bool\n    SubagentType  string\n    SubagentDesc  string\n}\n```\n\nHandle malformed JSON lines gracefully: log warning, skip line, continue.\n\n**Verify:** unit tests with synthetic JSONL covering all message types. Test: valid session, empty session, tool-result-only session, session with away_summary, session with system-reminder tags in user text.\n\n### 2.2 Sub-agent parsing\n\n**File:** `internal/session/parse.go` (extend)\n\nAdd function to parse sub-agent conversations:\n\n1. Check if `<uuid>/subagents/` directory exists.\n2. List `agent-*.jsonl` files.\n3. For each, read the corresponding `agent-*.meta.json` for `agentType` and `description`.\n4. Parse the sub-agent JSONL using the same parser logic.\n5. Return sub-agent turn pairs with `IsSubagent: true` and the metadata fields populated.\n\n**Verify:** unit tests with synthetic sub-agent JSONL + meta.json files.\n\n### 2.3 Transcript builder\n\n**File:** `internal/session/transcript.go`\n\nConvert `ParsedSession` to a plaintext transcript string:\n\n```\nHuman: <text>\nAssistant: <text>\n[Tools: Read, Edit]\n\n[Session summary: <away_summary text>]\n\n--- Subagent: Explore — \"description\" ---\nHuman: <text>\nAssistant: <text>\n--- End subagent ---\n```\n\nRules:\n- Tool-result-only user messages are already filtered out by the parser.\n- `[Tools: ...]` line appears only when the turn had tool_use blocks.\n- `[Session summary: ...]` for away_summary entries (inserted inline at the position they appeared).\n- Sub-agent turns are delimited with `---` markers.\n\n**Verify:** unit tests with known ParsedSession → expected transcript string.\n\n### 2.4 Session-level gate\n\n**File:** `internal/session/parse.go` (extend)\n\nAdd validation function:\n\n```go\nfunc (s *ParsedSession) IsIndexable() bool\n```\n\nReturns true if:\n- `len(TurnPairs) >= 2` (counting only non-subagent pairs for the minimum, or all pairs — TBD based on what feels right)\n- `TotalAssistantChars >= 200`\n\n**Verify:** unit tests with edge cases: 1 turn pair (reject), 2 pairs with 150 chars (reject), 2 pairs with 300 chars (accept).\n\n---\n\n## Phase 3: Chunking\n\n### 3.1 Transcript chunking function\n\n**File:** `internal/store/chunk.go`\n\nAdd `chunkTranscript(content string, linesPerChunk int) []Chunk`:\n\n- Split on `Human:` turn boundaries (not arbitrary lines).\n- Sliding window of ~4 turn pairs with 1 turn pair overlap.\n- Each chunk title: `Session <datetime> | Turns <start>-<end> | Tools: <names>`. When sub-agent turns are present: append `| Subagent: <type>`.\n- Tool names and subagent info are extracted from the transcript text itself (parse `[Tools: ...]` lines and `--- Subagent: ... ---` markers).\n- Chunks exceeding `maxChunkBytes` are split using existing `splitOversized`.\n- Content type on all chunks: `\"session\"`.\n\n**File:** `internal/store/index.go`\n\n- Update `chunkContent` to route `\"session\"` content type to `chunkTranscript`.\n\n**Verify:** unit tests with a multi-turn transcript. Verify: correct window boundaries, overlap, title generation, oversized splitting.\n\n---\n\n## Phase 4: Sweep Integration\n\n### 4.1 Session directory discovery\n\n**New file:** `internal/session/sweep.go`\n\nAdd function to derive the Claude Code session directory:\n\n```go\nfunc SessionDir(projectDir string) (string, error)\n```\n\n- Compute absolute path of `projectDir`.\n- Mangle: replace `/` and `.` with `-`.\n- Construct: `~/.claude/projects/<mangled>/`.\n- Verify directory exists. Return error if not.\n\n**Verify:** unit test with known project paths → expected directory names. Test the `.` replacement (e.g., paths containing `.config`).\n\n### 4.2 Mtime gate\n\n**File:** `internal/session/sweep.go`\n\nAdd the mtime comparison logic:\n\n1. Query all `session:` sources from the store → build `uuid → indexed_at` map.\n2. For each `.jsonl` file: extract UUID from filename, compute effective mtime as `max(file.mtime, subagents_dir.mtime)`.\n3. Compare against `indexed_at`. Skip if effective mtime <= indexed_at.\n\n**Verify:** unit tests with mocked file stats and store data. Test: new file (no existing source), unchanged file (skip), modified file (process), file with updated sub-agent dir (process).\n\n### 4.3 Sweep orchestrator\n\n**File:** `internal/session/sweep.go`\n\nAdd the main sweep function:\n\n```go\nfunc Sweep(store *store.ContentStore, projectDir string) (indexed int, skipped int, errors int)\n```\n\nOrchestrates: discovery → list files → mtime gate → parse → gate → transcript → index.\n\nLogs at info level: `\"session sweep complete\"` with indexed/skipped/error counts.\nLogs at warn level: individual parse failures.\n\n**Verify:** integration test with a temp directory containing synthetic session files. Verify: correct files indexed, mtime gate works, gate filters trivial sessions, errors are logged and skipped.\n\n### 4.4 Server startup integration\n\n**File:** `internal/server/server.go`\n\nIn `Serve()`, after `s.registerTools()` and before `stdio.Listen()`:\n\n```go\ngo func() {\n    ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n    defer cancel()\n    indexed, skipped, errs := session.Sweep(s.getStore(), s.projectDir)\n    if indexed > 0 || errs > 0 {\n        slog.Info(\"session sweep\", \"indexed\", indexed, \"skipped\", skipped, \"errors\", errs)\n    }\n}()\n```\n\n**Verify:** start the server with synthetic session files present, verify they get indexed. Start again, verify no re-indexing (mtime gate).\n\n---\n\n## Phase 5: CLI and Tool Updates\n\n### 5.1 MCP cleanup tool\n\n**File:** `internal/server/tool_cleanup.go`\n\n- Add `purge_session` boolean parameter to the tool schema.\n- When `purge_session` is true, call `store.PurgeSession(dryRun, sessionTTL)`.\n\n**Verify:** unit test: call cleanup with `purge_session=true`, verify only session sources are affected.\n\n### 5.2 CLI cleanup command\n\n**File:** `cmd/capy/cleanup.go`\n\n- Add `--kind` string flag (valid values: `\"ephemeral\"`, `\"session\"`, `\"\"` for all).\n- When `--kind` is set, run only the corresponding cleanup path.\n\n**Verify:** manual test: `./capy cleanup --kind session` with indexed session sources.\n\n### 5.3 Stats rendering\n\n**File:** `internal/server/tool_stats.go`\n\n- Update stats rendering to include session source count and fresh/stale breakdown.\n\n**Verify:** index some session sources, call `capy_stats`, verify session section appears.\n\n---\n\n## Phase 6: Final Verification\n\n### 6.1 Full test suite\n\nRun `make test` and `make test-race`. All existing tests must pass. No regressions.\n\n### 6.2 Integration test\n\nAdd an end-to-end test in `internal/server/integration_test.go`:\n1. Create synthetic session JSONL files in a temp directory.\n2. Boot a test server pointing at that directory.\n3. Trigger the sweep.\n4. Search for session content via the MCP tool handler.\n5. Verify results surface with correct labels and titles.\n6. Run cleanup, verify TTL eviction.\n\n### 6.3 Documentation\n\n- Update `CONTRIBUTING.md` if the new `internal/session/` package introduces patterns worth documenting.\n- Write ADR for the `KindSession` decision (ADR-019 or next available number).\n\n### 6.4 Code review\n\nRun `kk:review-code` on the final diff. Run `kk:review-spec` to verify implementation matches this design doc.\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1760,"cache_read_input_tokens":127899,"output_tokens":3887,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1760,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGZ6wRP9X2JLjekUc4X","type":"assistant","uuid":"ccac234a-ef90-449f-a259-eb89b232e3d5","timestamp":"2026-04-23T19:40:12.047Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"ccac234a-ef90-449f-a259-eb89b232e3d5","isSidechain":false,"promptId":"8f32cf08-e37b-4a9f-bf36-dbb9fa1721c8","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MzGdr5zKkWhwSnBnU2XwcD","type":"tool_result","content":"File created successfully at: /home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/implementation.md"}]},"uuid":"36d46cea-f032-4eae-ba4a-da77af75e6cc","timestamp":"2026-04-23T19:40:12.080Z","toolUseResult":{"type":"create","filePath":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/implementation.md","content":"# Sessionflow RAG — Implementation Plan\n\n> **Design:** [./design.md](./design.md)\n> **Issue:** [#24](https://github.com/serpro69/capy/issues/24)\n> **Created:** 2026-04-23\n\nThis plan is ordered for incremental development. Each task builds on the previous and can be verified independently. The developer should be familiar with Go and SQLite but may have no prior context on the capy codebase.\n\n## Prerequisites\n\nRead these files before starting:\n- `CONTRIBUTING.md` — build instructions, test patterns, project structure\n- `internal/store/types.go` — source kinds, chunk types, search/index result types\n- `internal/store/schema.go` — FTS5 schema\n- `internal/store/index.go` — `Index()` function, content_hash dedup, `chunkContent` routing\n- `internal/store/cleanup.go` — retention scoring, `cleanupEphemeral`, `Cleanup()`\n- `internal/store/chunk.go` — `chunkPlainText`, `chunkMarkdown`, splitting strategies\n- `internal/server/server.go` — `Server` struct, `Serve()`, `getStore()`, `ephemeralTTL()`\n- `internal/config/config.go` — `Config`, `CleanupConfig`, `DefaultConfig()`\n- `docs/adr/017-source-kind-separation.md` — why source kinds exist, the `IncludeKinds` design\n\nAll tests require `-tags fts5`. Use `make test` or `go test -tags fts5 -count=1 ./...`.\n\n---\n\n## Phase 1: Storage Foundation\n\n### 1.1 Add KindSession to types\n\n**File:** `internal/store/types.go`\n\n- Add `KindSession SourceKind = \"session\"` constant.\n- Update `Valid()` to return true for `KindSession`.\n- Add session-specific fields to `StoreStats`: `SessionSourceCount`, `SessionFreshCount`, `SessionStaleCount`.\n\n**Verify:** existing tests still pass (`go test -tags fts5 ./internal/store/...`). No behavioral change yet.\n\n### 1.2 Schema migration\n\n**File:** `internal/store/migrate.go`\n\nAdd a new migration that alters the CHECK constraint on `sources.kind` to accept `'session'`. SQLite does not support `ALTER TABLE ... ALTER CONSTRAINT`, so the migration must:\n\n1. Create a new table with the updated CHECK constraint.\n2. Copy all data from the old table.\n3. Drop the old table.\n4. Rename the new table.\n\nFollow the existing migration pattern in `migrate.go`. The migration number should be the next sequential one.\n\n**Verify:** `go test -tags fts5 ./internal/store/...` — migration applies cleanly. Open a test DB, insert a source with `kind = 'session'`, confirm no constraint violation.\n\n### 1.3 Config: SessionTTLDays\n\n**File:** `internal/config/config.go`\n\n- Add `SessionTTLDays int` to `CleanupConfig` with toml tag `session_ttl_days`.\n- Set default to 60 in `DefaultConfig()`.\n\n**File:** `internal/config/loader.go`\n\n- Add validation: `SessionTTLDays` must be >= 1. Reject with error if < 1.\n\n**File:** `internal/server/server.go`\n\n- Add `sessionTTL()` method mirroring `ephemeralTTL()`: resolves TTL from config with 60-day fallback.\n\n**Verify:** `go test -tags fts5 ./internal/config/...` — config loads with default, rejects invalid values.\n\n### 1.4 Cleanup: Generalize TTL-based eviction\n\n**File:** `internal/store/cleanup.go`\n\n- Rename `cleanupEphemeral` to `cleanupByTTL(kind SourceKind, ttl time.Duration)`. The only change: the `WHERE kind = ?` parameter becomes the `kind` argument instead of hardcoded `KindEphemeral`.\n- Update `Cleanup()` to call `cleanupByTTL` twice: once for `KindEphemeral` with ephemeral TTL, once for `KindSession` with session TTL.\n- Update `PurgeEphemeral` to call `cleanupByTTL(KindEphemeral, ttl)`.\n- Add `PurgeSession(dryRun bool, ttl time.Duration)` that calls `cleanupByTTL(KindSession, ttl)`.\n- Update `ClassifySources` to handle `KindSession` with fresh/stale bucketing using session TTL.\n- Update `Stats()` to accept both TTLs (or a TTL map) and populate session counters.\n\n**Verify:** `go test -tags fts5 ./internal/store/...` — existing ephemeral cleanup tests pass. Add tests for session TTL cleanup: index a session-kind source, advance clock past TTL, verify eviction.\n\n### 1.5 Search: Update default IncludeKinds\n\n**File:** `internal/server/tool_search.go`\n\n- Update the default `IncludeKinds` from `[KindDurable]` to `[KindDurable, KindSession]`.\n\n**File:** `internal/server/intent_search.go` (if applicable)\n\n- Verify intent search does not need session kind changes (it writes ephemeral, searches durable).\n\n**Verify:** index a session-kind source manually, search for its content, verify it appears in results. Verify ephemeral sources are still excluded by default.\n\n---\n\n## Phase 2: Session Parsing\n\n### 2.1 JSONL parser\n\n**New file:** `internal/session/parse.go`\n\nCreate a session JSONL parser that reads a file and produces a filtered transcript. The parser:\n\n1. Reads the file line by line.\n2. Parses each line as JSON.\n3. Routes on `type` field:\n   - `\"user\"`: extract text content (string or text blocks from array). Skip tool_result-only messages. Skip messages starting with `/`. Strip `<system-reminder>` tags.\n   - `\"assistant\"`: extract text from `text` blocks. Extract tool names from `tool_use` blocks. Skip `thinking` blocks.\n   - `\"system\"` with `subtype == \"away_summary\"`: extract `content` field.\n   - All other types: skip.\n4. Builds turn pairs: a turn pair is a human text message followed by assistant text response(s). Tool names from assistant tool_use blocks are collected per turn.\n5. Extracts session metadata: first user message timestamp (for the label datetime), session UUID (from `sessionId` field or filename).\n\n**Output type:**\n\n```go\ntype ParsedSession struct {\n    SessionID  string\n    StartTime  time.Time\n    TurnPairs  []TurnPair\n    TotalAssistantChars int\n}\n\ntype TurnPair struct {\n    HumanText     string\n    AssistantText string\n    ToolNames     []string\n    IsSubagent    bool\n    SubagentType  string\n    SubagentDesc  string\n}\n```\n\nHandle malformed JSON lines gracefully: log warning, skip line, continue.\n\n**Verify:** unit tests with synthetic JSONL covering all message types. Test: valid session, empty session, tool-result-only session, session with away_summary, session with system-reminder tags in user text.\n\n### 2.2 Sub-agent parsing\n\n**File:** `internal/session/parse.go` (extend)\n\nAdd function to parse sub-agent conversations:\n\n1. Check if `<uuid>/subagents/` directory exists.\n2. List `agent-*.jsonl` files.\n3. For each, read the corresponding `agent-*.meta.json` for `agentType` and `description`.\n4. Parse the sub-agent JSONL using the same parser logic.\n5. Return sub-agent turn pairs with `IsSubagent: true` and the metadata fields populated.\n\n**Verify:** unit tests with synthetic sub-agent JSONL + meta.json files.\n\n### 2.3 Transcript builder\n\n**File:** `internal/session/transcript.go`\n\nConvert `ParsedSession` to a plaintext transcript string:\n\n```\nHuman: <text>\nAssistant: <text>\n[Tools: Read, Edit]\n\n[Session summary: <away_summary text>]\n\n--- Subagent: Explore — \"description\" ---\nHuman: <text>\nAssistant: <text>\n--- End subagent ---\n```\n\nRules:\n- Tool-result-only user messages are already filtered out by the parser.\n- `[Tools: ...]` line appears only when the turn had tool_use blocks.\n- `[Session summary: ...]` for away_summary entries (inserted inline at the position they appeared).\n- Sub-agent turns are delimited with `---` markers.\n\n**Verify:** unit tests with known ParsedSession → expected transcript string.\n\n### 2.4 Session-level gate\n\n**File:** `internal/session/parse.go` (extend)\n\nAdd validation function:\n\n```go\nfunc (s *ParsedSession) IsIndexable() bool\n```\n\nReturns true if:\n- `len(TurnPairs) >= 2` (counting only non-subagent pairs for the minimum, or all pairs — TBD based on what feels right)\n- `TotalAssistantChars >= 200`\n\n**Verify:** unit tests with edge cases: 1 turn pair (reject), 2 pairs with 150 chars (reject), 2 pairs with 300 chars (accept).\n\n---\n\n## Phase 3: Chunking\n\n### 3.1 Transcript chunking function\n\n**File:** `internal/store/chunk.go`\n\nAdd `chunkTranscript(content string, linesPerChunk int) []Chunk`:\n\n- Split on `Human:` turn boundaries (not arbitrary lines).\n- Sliding window of ~4 turn pairs with 1 turn pair overlap.\n- Each chunk title: `Session <datetime> | Turns <start>-<end> | Tools: <names>`. When sub-agent turns are present: append `| Subagent: <type>`.\n- Tool names and subagent info are extracted from the transcript text itself (parse `[Tools: ...]` lines and `--- Subagent: ... ---` markers).\n- Chunks exceeding `maxChunkBytes` are split using existing `splitOversized`.\n- Content type on all chunks: `\"session\"`.\n\n**File:** `internal/store/index.go`\n\n- Update `chunkContent` to route `\"session\"` content type to `chunkTranscript`.\n\n**Verify:** unit tests with a multi-turn transcript. Verify: correct window boundaries, overlap, title generation, oversized splitting.\n\n---\n\n## Phase 4: Sweep Integration\n\n### 4.1 Session directory discovery\n\n**New file:** `internal/session/sweep.go`\n\nAdd function to derive the Claude Code session directory:\n\n```go\nfunc SessionDir(projectDir string) (string, error)\n```\n\n- Compute absolute path of `projectDir`.\n- Mangle: replace `/` and `.` with `-`.\n- Construct: `~/.claude/projects/<mangled>/`.\n- Verify directory exists. Return error if not.\n\n**Verify:** unit test with known project paths → expected directory names. Test the `.` replacement (e.g., paths containing `.config`).\n\n### 4.2 Mtime gate\n\n**File:** `internal/session/sweep.go`\n\nAdd the mtime comparison logic:\n\n1. Query all `session:` sources from the store → build `uuid → indexed_at` map.\n2. For each `.jsonl` file: extract UUID from filename, compute effective mtime as `max(file.mtime, subagents_dir.mtime)`.\n3. Compare against `indexed_at`. Skip if effective mtime <= indexed_at.\n\n**Verify:** unit tests with mocked file stats and store data. Test: new file (no existing source), unchanged file (skip), modified file (process), file with updated sub-agent dir (process).\n\n### 4.3 Sweep orchestrator\n\n**File:** `internal/session/sweep.go`\n\nAdd the main sweep function:\n\n```go\nfunc Sweep(store *store.ContentStore, projectDir string) (indexed int, skipped int, errors int)\n```\n\nOrchestrates: discovery → list files → mtime gate → parse → gate → transcript → index.\n\nLogs at info level: `\"session sweep complete\"` with indexed/skipped/error counts.\nLogs at warn level: individual parse failures.\n\n**Verify:** integration test with a temp directory containing synthetic session files. Verify: correct files indexed, mtime gate works, gate filters trivial sessions, errors are logged and skipped.\n\n### 4.4 Server startup integration\n\n**File:** `internal/server/server.go`\n\nIn `Serve()`, after `s.registerTools()` and before `stdio.Listen()`:\n\n```go\ngo func() {\n    ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n    defer cancel()\n    indexed, skipped, errs := session.Sweep(s.getStore(), s.projectDir)\n    if indexed > 0 || errs > 0 {\n        slog.Info(\"session sweep\", \"indexed\", indexed, \"skipped\", skipped, \"errors\", errs)\n    }\n}()\n```\n\n**Verify:** start the server with synthetic session files present, verify they get indexed. Start again, verify no re-indexing (mtime gate).\n\n---\n\n## Phase 5: CLI and Tool Updates\n\n### 5.1 MCP cleanup tool\n\n**File:** `internal/server/tool_cleanup.go`\n\n- Add `purge_session` boolean parameter to the tool schema.\n- When `purge_session` is true, call `store.PurgeSession(dryRun, sessionTTL)`.\n\n**Verify:** unit test: call cleanup with `purge_session=true`, verify only session sources are affected.\n\n### 5.2 CLI cleanup command\n\n**File:** `cmd/capy/cleanup.go`\n\n- Add `--kind` string flag (valid values: `\"ephemeral\"`, `\"session\"`, `\"\"` for all).\n- When `--kind` is set, run only the corresponding cleanup path.\n\n**Verify:** manual test: `./capy cleanup --kind session` with indexed session sources.\n\n### 5.3 Stats rendering\n\n**File:** `internal/server/tool_stats.go`\n\n- Update stats rendering to include session source count and fresh/stale breakdown.\n\n**Verify:** index some session sources, call `capy_stats`, verify session section appears.\n\n---\n\n## Phase 6: Final Verification\n\n### 6.1 Full test suite\n\nRun `make test` and `make test-race`. All existing tests must pass. No regressions.\n\n### 6.2 Integration test\n\nAdd an end-to-end test in `internal/server/integration_test.go`:\n1. Create synthetic session JSONL files in a temp directory.\n2. Boot a test server pointing at that directory.\n3. Trigger the sweep.\n4. Search for session content via the MCP tool handler.\n5. Verify results surface with correct labels and titles.\n6. Run cleanup, verify TTL eviction.\n\n### 6.3 Documentation\n\n- Update `CONTRIBUTING.md` if the new `internal/session/` package introduces patterns worth documenting.\n- Write ADR for the `KindSession` decision (ADR-019 or next available number).\n\n### 6.4 Code review\n\nRun `kk:review-code` on the final diff. Run `kk:review-spec` to verify implementation matches this design doc.\n","structuredPatch":[],"originalFile":null,"userModified":false},"sourceToolAssistantUUID":"ccac234a-ef90-449f-a259-eb89b232e3d5","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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 {"parentUuid":"54b718e0-10c9-4700-af72-c1c84fda2783","isSidechain":false,"message":{"model":"claude-opus-4-6","id":"msg_01Xpi72g1vUVzKTo8s1G8Fan","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Lgh1z6GPNBbpRoXGwYbhX5","name":"Write","input":{"file_path":"/home/sergio/Projects/personal/capy/docs/wip/sessionflow-rag/tasks.md","content":"# Tasks: Sessionflow RAG\n\n> Design: [./design.md](./design.md)\n> Implementation: [./implementation.md](./implementation.md)\n> Status: pending\n> Created: 2026-04-23\n\n## Task 1: Storage foundation — KindSession, migration, config\n- **Status:** pending\n- **Depends on:** —\n- **Docs:** [implementation.md#phase-1-storage-foundation](./implementation.md#phase-1-storage-foundation)\n\n### Subtasks\n- [ ] 1.1 Add `KindSession SourceKind = \"session\"` to `internal/store/types.go`, update `Valid()`, add session fields to `StoreStats`\n- [ ] 1.2 Add schema migration in `internal/store/migrate.go` to update CHECK constraint on `sources.kind` to accept `'session'`\n- [ ] 1.3 Add `SessionTTLDays int` to `CleanupConfig` in `internal/config/config.go` (default 60), add validation in `loader.go`, add `sessionTTL()` to server\n- [ ] 1.4 Generalize `cleanupEphemeral` → `cleanupByTTL(kind, ttl)` in `internal/store/cleanup.go`, update `Cleanup()` to call it for both ephemeral and session, add `PurgeSession()`, update `ClassifySources` and `Stats()` for session kind\n- [ ] 1.5 Update default `IncludeKinds` in `internal/server/tool_search.go` from `[KindDurable]` to `[KindDurable, KindSession]`\n- [ ] 1.6 Write tests for all above: migration applies, session kind accepted, TTL cleanup works, search includes sessions\n\n## Task 2: Session JSONL parser\n- **Status:** pending\n- **Depends on:** —\n- **Docs:** [implementation.md#phase-2-session-parsing](./implementation.md#phase-2-session-parsing)\n\n### Subtasks\n- [ ] 2.1 Create `internal/session/parse.go` with JSONL parser: line-by-line reading, type routing, text extraction, tool name extraction, system-reminder stripping\n- [ ] 2.2 Define `ParsedSession` and `TurnPair` types with session metadata (SessionID, StartTime, TotalAssistantChars)\n- [ ] 2.3 Add sub-agent parsing: discover `<uuid>/subagents/` directory, parse `agent-*.jsonl` and `agent-*.meta.json`, return sub-agent turn pairs with metadata\n- [ ] 2.4 Add `IsIndexable()` session-level gate: min 2 turn pairs, min 200 chars assistant text\n- [ ] 2.5 Write unit tests in `internal/session/parse_test.go` with synthetic JSONL fixtures covering: valid session, empty session, tool-result-only session, away_summary, system-reminder tags, sub-agent conversations, malformed JSON lines\n\n## Task 3: Transcript builder and chunking\n- **Status:** pending\n- **Depends on:** Task 2\n- **Docs:** [implementation.md#phase-2-session-parsing](./implementation.md#phase-2-session-parsing), [implementation.md#phase-3-chunking](./implementation.md#phase-3-chunking)\n\n### Subtasks\n- [ ] 3.1 Create `internal/session/transcript.go` to convert `ParsedSession` → plaintext transcript string with `Human:`/`Assistant:` format, `[Tools: ...]` lines, `[Session summary: ...]` entries, and `--- Subagent ---` delimiters\n- [ ] 3.2 Add `chunkTranscript` function to `internal/store/chunk.go`: sliding window of ~4 turn pairs, 1-pair overlap, split on `Human:` boundaries, title generation with datetime/turn range/tools/subagent info\n- [ ] 3.3 Update `chunkContent` in `internal/store/index.go` to route `\"session\"` content type to `chunkTranscript`\n- [ ] 3.4 Write unit tests: transcript builder output, chunk boundaries, overlap, title format, oversized chunk splitting\n\n## Task 4: Sweep mechanism\n- **Status:** pending\n- **Depends on:** Task 1, Task 2, Task 3\n- **Docs:** [implementation.md#phase-4-sweep-integration](./implementation.md#phase-4-sweep-integration)\n\n### Subtasks\n- [ ] 4.1 Create `internal/session/sweep.go` with `SessionDir(projectDir string)` — path mangling (replace `/` and `.` with `-`), directory existence check\n- [ ] 4.2 Add mtime gate logic: query `session:` sources from store, build `uuid → indexed_at` map, compare `max(file.mtime, subagents_dir.mtime)` against indexed_at\n- [ ] 4.3 Add `Sweep(store, projectDir)` orchestrator: discovery → list → mtime gate → parse → gate → transcript → index. Log results.\n- [ ] 4.4 Integrate into `Server.Serve()` as background goroutine with 30s context timeout\n- [ ] 4.5 Write unit tests in `internal/session/sweep_test.go`: directory derivation, mtime gate logic. Write integration test with temp directory of synthetic session files.\n\n## Task 5: CLI and tool updates\n- **Status:** pending\n- **Depends on:** Task 1, Task 4\n- **Docs:** [implementation.md#phase-5-cli-and-tool-updates](./implementation.md#phase-5-cli-and-tool-updates)\n\n### Subtasks\n- [ ] 5.1 Add `purge_session` boolean parameter to `capy_cleanup` MCP tool in `internal/server/tool_cleanup.go`\n- [ ] 5.2 Add `--kind` string flag to `cmd/capy/cleanup.go` CLI command\n- [ ] 5.3 Update stats rendering in `internal/server/tool_stats.go` to include session source count and fresh/stale breakdown\n- [ ] 5.4 Write tests for cleanup with purge_session, stats with session sources\n\n## Task 6: Final verification\n- **Status:** pending\n- **Depends on:** Task 1, Task 2, Task 3, Task 4, Task 5\n\n### Subtasks\n- [ ] 6.1 Run `test` skill to verify all tasks — full test suite (`make test`, `make test-race`), integration tests, edge cases\n- [ ] 6.2 Add end-to-end integration test in `internal/server/integration_test.go`: synthetic sessions → sweep → search → verify results → cleanup → verify eviction\n- [ ] 6.3 Run `document` skill to write ADR-019 for KindSession decision, update CONTRIBUTING.md if needed\n- [ ] 6.4 Run `review-code` skill to review the implementation\n- [ ] 6.5 Run `review-spec` skill to verify implementation matches design and implementation docs\n"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3930,"cache_read_input_tokens":129659,"output_tokens":1831,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3930,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CaMGeaBuQA6bucWcC4FFt","type":"assistant","uuid":"d15a95d3-724d-47f7-ab96-5f00aef960c4","timestamp":"2026-04-23T19:40:41.284Z","userType":"external","entrypoint":"cli","cwd":"/home/sergio/Projects/personal/capy","sessionId":"b5ee5362-8700-4c9c-8278-51cb58c2e096","version":"2.1.116","gitBranch":"master"}
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