技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
codex-autoresearch【数据与研究】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.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Improve a repository through repeated, reversible experiments:
hypothesize -> change -> measure -> learn -> keep or revert -> repeat
Codex chooses hypotheses and makes code changes. The control script owns measurement, commits, rollback, and the event history.
Resolve <control> to this skill's own scripts/autoresearch.py; do not assume it is installed in the target repository.
For a status or results request, run the corresponding command directly:
| Request | Command |
|---|---|
| Status | python3 <control> status --repo <repo> |
| History | python3 <control> history --repo <repo> |
| TSV export | python3 <control> history --repo <repo> --format tsv |
| HTML report | python3 <control> report --repo <repo> |
Report the requested result without starting or resuming experiments. Return the generated path for an HTML report.
Before starting or resuming an experiment, read the applicable workflow unless it is already in context:
complete, no Goal is needed.finish to finalize each coherent experiment. Do not manually commit, revert, or edit run artifacts during an active run.complete; an iteration limit, error, or external blocker has its own status.Foreground continuation belongs to the official Codex Goal. Background continuation belongs to the detached controller. An already launched background worker follows its supplied experiment contract, without starting a new launch flow.