Behavioral guardrails for LLM coding derived from Andrej Karpathy's observations on AI coding pitfalls. Apply whenever writing, editing, refactoring, debugging, or reviewing code — any language, any stack. These principles should be active any time Claude touches code.
Review pending skill suggestions collected by the background observer. Use when the user wants to see, approve, reject, or apply pattern suggestions that the observer flagged during past sessions.
Autonomous 3x/day AI intel sweep — fetches HackerNews, GitHub Trending, Google AI Blog, ArXiv, X/Twitter, and star-history.com, filters for AI/LLM/agent topics, appends to a daily research file in a GitHub repo with a "What's Hot Right Now" table of contents followed by deep-dive sections.
Draft a LinkedIn post or newsletter section grounded in real data from the latest AI intel report. Invoke when the user says "write a LinkedIn post", "draft a post about [topic]", "write a newsletter section", "curate content for me", "turn today's intel into a post", or "I want to post about [X]". Always reads the…
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originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: