LuminairPrime

The acraflow middleware pipeline — token-conservation features & enhancements

A continuation of "The acraflow middleware worker apparatus" with a deep inventory of token-conservation features — the implemented mechanisms that realize the middleware's design. This enhanced gist catalogs the full repertoire of levers, handlers, components, and directives that make token-efficient solving possible: from cached grounding to deterministic routing to synthetic pre-staging, every feature that saves tokens (or ensures they're spent wisely).

0. The core idea (recalled from the architecture)

Once a problem is solved, re-encountering it should cost no model call.

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

name: setup-llms-txt description: | Create and configure llms.txt for any website or project. Analyzes project structure, generates a spec-compliant llms.txt, and places it in the correct location for your framework. Optionally generates llms-full.txt as a companion file. Use when setting up llms.txt, updating an existing one, or making a site LLM-friendly. triggers:

description	Project work through one DAG. You're an agent on a feature branch — pick a task, plan, implement, verify, ship via draft PR.

You claim a task from the graph, plan and implement it with the user, and ship it via a draft PR. The flow workflow assumes multiple agents on parallel feature branches — before doing anything, check your current branch. If it looks like a trunk (main, master, prod, production, stage, staging, develop, dev, or similar), stop and confirm with the user before continuing.

On activation, run scripts/flow-sync.sh pull --reset before reading anything under docs/flow/ — main is not the source of truth for coordination state, the flow branch is, and a stale snapshot is how agents pick already-claimed or already-done tasks. --reset is correct for this first pull because your feature branch was just cut from main and has nothing of your own to preserve in docs/flow/ yet — let it adopt the live state wholesale rather than wading t

Codex Execution Plans (ExecPlans):

This document describes the requirements for an execution plan ("ExecPlan"), a design document that a coding agent can follow to deliver a working feature or system change. Treat the reader as a complete beginner to this repository: they have only the current working tree and the single ExecPlan file you provide. There is no memory of prior plans and no external context.

How to use ExecPlans and PLANS.md

When authoring an executable specification (ExecPlan), follow PLANS.md to the letter. If it is not in your context, refresh your memory by reading the entire PLANS.md file. Be thorough in reading (and re-reading) source material to produce an accurate specification. When creating a spec, start from the skeleton and flesh it out as you do your research.

When implementing an executable specification (ExecPlan), do not prompt the user for "next steps"; simply proceed to the next milestone. Keep all sections up to date, add or split entries in the list at every stoppi

Prompt: Scaffold a Project from `PRD.md`

Use the prompt below with a coding agent to read a PRD.md file and scaffold a project repository, including the recommended files and built-in guidance for how humans should complete any missing details.

Recommended use

Give the agent this prompt in a repository that contains a PRD.md at the root.
The agent should then inspect PRD.md, choose a reasonable project structure, create the starter files, and place clear fill-in guidance where the PRD does not yet specify enough.

🧠 Ultimate LLM Codebase Brain Dump Prompt

This prompt is designed for GPT-5, Claude Opus 4.1, Cursor, Claude Code, and cursor-agent to perform a deep, structured analysis of any codebase without pasting the entire repo into chat.

It guides the LLM to:

Browse and discover the codebase using built-in repo tools
Read only the necessary files in intelligent order
Analyze the system at high, mid, and low levels
Identify features, their business purposes, how they work, and how they interact
Output a complete master knowledge document inside codebase-analysis-docs/

Garlic OS Tips (Windows-based)

GarlicOS Cookbook

Follow these instructions for an easy way to get up and going quickly! These are complete instructions, and will be the easiest way to get started on a new RG35XX.

Set up SD Card

Get a high quality SD (e.g. SanDisk Extreme) card, 128GB or larger, 256GB is recommended. Don't skimp here, they're cheap, and don't use the card that comes with the RG35XX as it's crap.

	{#---------------------------------------------------------------------
	custom_pub_chat_template_qwen36.jinja
	=====================================
	A public, harness-friendly fork of Qwen's Qwen3.6-27B chat template,
	tuned for open-source agentic coding harnesses like:
	- anomalyco/opencode (https://github.com/anomalyco/opencode)
	- earendil-works/pi (https://github.com/earendil-works/pi)
	- openclaw, OpenHarness, similar Claude-Code-style harnesses

	WHY THIS FORK EXISTS

	{#---------------------------------------------------------------------
	custom_pub_chat_template_gemma4.jinja
	=====================================
	A public, harness-friendly fork of Google's Gemma 4 chat template,
	tuned for open-source agentic coding harnesses like:
	- anomalyco/opencode (https://github.com/anomalyco/opencode)
	- earendil-works/pi (https://github.com/earendil-works/pi)
	- openclaw, OpenHarness, similar Claude-Code-style harnesses

	WHY THIS FORK EXISTS