Autoresearch

This is an autonomous experiment loop that tries code changes, measures results, and automatically keeps or discards them based on whether your metric improved. You define the goal (speed, memory, test coverage, whatever), provide the measurement command, and it runs unsupervised, making focused edits and reverting anything that doesn't help. Inspired by Karpathy's ML training loop but generalized to any programming task. It's surprisingly opinionated about simplicity, won't bloat your code for marginal gains, and requires git since every experiment is a commit that gets kept or reset. Best for iterative optimization where you have a clear metric. Completely wrong for one-off fixes or anything you can't measure numerically.

Install to Claude Code

npx -y skills add github/awesome-copilot --skill autoresearch --agent claude-code