name: tufte-viz description: | Ideate and critique data visualizations using Edward Tufte's principles from "The Visual Display of Quantitative Information." Use this skill when: (1) Designing new data visualizations or charts (2) Critiquing or improving existing visualizations (3) Reviewing dashboards or reports for graphical integrity (4) Deciding between visualization approaches (5) Reducing chartjunk or improving data-ink ratio (6) Planning small multiples or high-density displays
| -- ============================================================================ | |
| -- MINI TERMINATION CHECKER VIA FOLD GENERATION | |
| -- finding the legal recursive calls of a clause, without comparing sizes | |
| -- ============================================================================ | |
| -- | |
| -- Everything here is written in the term language and nothing else: | |
| -- | |
| -- x a variable | |
| -- λx. e a lambda | |
| -- (f x) application (n-ary: (f x y)) |
| #!/usr/bin/env bash | |
| # Hook: ensure-fresh-branch.sh | |
| # Fires on SubagentStart(Plan). | |
| # Ensures we're on a fresh branch before starting any new task planning. | |
| # save as .claude/hooks/ensure-fresh-branch.sh | |
| # | |
| # Behavior: | |
| # - Non-Plan subagent: no-op (exit 0 immediately) | |
| # - On master/main: fetches latest, creates claude/task-<slug> branch | |
| # - On a branch with a merged PR: switches to master, creates new branch |
| description | Interview me about the plan | |
|---|---|---|
| argument-hint |
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| model | opus |
Read this plan file $1 and interview me in detail using the AskUserQuestionTool about literally anything: technical implementation, UI & UX, concerns, tradeoffs, etc. but make sure the questions are not obvious.
how is the morph warp search tool working for you so far? Is it reliable and effective at finding relevant code? Use ultrathink
● Honestly, I haven't actually used the mcp__morph-mcp__warp_grep tool in this session at all. Let me reflect on why and give you a candid assessment:
My Actual Tool Usage This Session
I defaulted to the standard tools:
- Grep for pattern searches (e.g., screenshot in deployment-monitor.sh)
- Read for reading specific files I already knew about
| # /// script | |
| # dependencies = [ "transformers", "accelerate" ] | |
| # /// | |
| # run on 2xH200 rented from primeintellect.ai | |
| import gc | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer |
| This is a debugging challenge. | |
| Read the document below, and identify the bug. | |
| --- | |
| # The Interaction Calculus | |
| The Interaction Calculus (IC) is term rewriting system inspired by the Lambda | |
| Calculus (λC), but with some major differences: | |
| 1. Vars are affine: they can only occur up to one time. |
| // First, let's look at the traditional visitor pattern | |
| // This is how we might implement a simple expression evaluator | |
| // Traditional Visitor Pattern | |
| namespace Traditional { | |
| // Abstract base class for expressions | |
| abstract class Expr { | |
| abstract accept<T>(visitor: ExprVisitor<T>): T; | |
| } |
Relax, I only have one Sunday to work on idea, literally my weekend project. So I tried Deepseek to see if it can help. Surprisingly, it works and it saves me another weekend...
Just chat.deepseek.com (cost = free) with prompts adapted from this gist.
| You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis. | |
| ## Core Principles | |
| 1. EXPLORATION OVER CONCLUSION | |
| - Never rush to conclusions | |
| - Keep exploring until a solution emerges naturally from the evidence | |
| - If uncertain, continue reasoning indefinitely | |
| - Question every assumption and inference |