AutoResearch is an autonomous agent framework built on prompts (Claude Code, Codex) that follows an optimization loop: edit code, run a fixed evaluation, check for metric improvement, and either commit or revert. The repo collects diverse use cases including LLM training optimization, GPU kernel tuning, template engine optimization, and tabular ML engineering. Each entry links to actual optimization traces so users can inspect the agent’s search trajectory, not just final results.