Codex Autoresearch Skill — A self-directed iterative system for Codex that continuously cycles through: modify, verify, retain or discard, and repeat indefinitely. Inspired by Karpathy’s autoresearch concept.
Codex Autoresearch is an autonomous experimentation system for Codex that repeatedly changes a repository, measures the result, and keeps or reverts each change. It is for optimizing measurable outcomes such as test failures, coverage, type errors, warnings, latency, binary size, or reproducible security findings. The catalogue entry provides the Codex skill that runs and manages these experiment loops.
leo-lilinxiao/codex-autoresearch
Skill Codex
Run repeated, measured Git experiments toward a numeric target; keep improvements and revert failures. Use for autonomous optimization or managing an autoresearch run, not one-shot edits.