autoresearch
FeaturedStateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior
AI & Automation 39,098 stars
3499 forks Updated today MIT
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Skill Content
<Purpose>
Autoresearch is a stateful skill for bounded, evaluator-driven iterative improvement. It owns one mission at a time, keeps iterating through non-passing results, records each evaluation and decision as durable artifacts, and stops only when an explicit max-runtime ceiling or another explicit terminal condition is reached.
</Purpose>
<Use_When>
- You already have a mission and evaluator from `/deep-interview --autoresearch`
- You want persistent single-mission improvement with strict evaluation
- You need durable experiment logs under `.omc/autoresearch/`
- You want a supported path for periodic reruns via Claude Code native cron
</Use_When>
<Do_Not_Use_When>
- You need evaluator generation at runtime — use `/deep-interview --autoresearch` first
- You need multiple missions orchestrated together — v1 forbids that
- You want the deprecated `omc autoresearch` CLI flow — it is no longer authoritative
</Do_Not_Use_When>
<Contract>
- Single-mission only in v1
- Mission setup/evaluator generation stays in `deep-interview --autoresearch`
- Evaluator output must be structured JSON with required boolean `pass` and optional numeric `score`
- Non-passing iterations do **not** stop the run
- Stop conditions are explicit and bounded, with max-runtime as the primary strict stop hook
</Contract>
<Required_Artifacts>
Canonical persistent storage lives under `.omc/autoresearch/<mission-slug>/` and/or `.omc/logs/autoresearch/<run-id>/`.
Minimum required artifacts:
- mission spec
...
Details
- Author
- Yeachan-Heo
- Repository
- Yeachan-Heo/oh-my-claudecode
- Created
- 8 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
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