I analyzed 200+ versions of Claude Code updates and context optimization papers to build AgentLint. It runs 33 data-backed checks to ensure your codebase is "AI-Ready"—slashing hallucinations and boosting agent reasoning by optimizing repo structure.
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Maker
📌
Hey PH! 👋
I’m the maker of AgentLint.
I’ve been obsessed with how AI agents "read" our code. I noticed that even the best models like Claude 3.5 or GPT-4 fail when the repo structure is noisy or lacks clear context.
To find the "perfect repo" formula, I went down a deep rabbit hole:
I meticulously analyzed over 200 versions of Claude Code updates to see how its internal prompting and context-gathering rules evolved.
I cross-referenced this with the latest research papers on Long-Context window efficiency.
The result is AgentLint. Instead of manual cleanup, it automates 33 specific checks to ensure your repo is primed for AI reasoning. No more "I don't have enough context" or weird hallucinations because of a messy file tree.
It's a tool I built to save my own "vibe coding" sessions, and I hope it helps you too! Would love to hear your feedback. 🚀