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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.
codex-autoresearch is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # Codex Autoresearch Improve a repository through repeated, reversible experiments: `hypothesize -> change -> measure -> learn -> keep or revert -> repeat` Code. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding codex-autoresearch to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install leo-lilinxiao/codex-autoresearchReview the upstream source before running this command.
Scan coverage: Install metadata and the indexed document body.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
# Codex Autoresearch Improve a repository through repeated, reversible experiments: `hypothesize -> change -> measure -> learn -> keep or revert -> repeat` Codex chooses hypotheses