autoresearchlisted

# Autoresearch Skill Autoresearch means one bounded target, one external metric, one keep/revert loop, one append-only log. ## When to use - prompt optimization - worker routing - tool behavior - evaluation harnesses - any repo-local target that can be measured honestly ## Process 1. Read `atris/experiments/<slug>/program.md` 2. Confirm the target is bounded 3. Run the baseline with `measure.py` 4. Apply one candidate change 5. Rerun the metric 6. Keep only if the score improves 7. Write the outcome to `results.tsv` 8. Revert losses ## Rules - external metric only - no unlogged keeps - no broad refactors inside an experiment - one experiment pack = one target - if variance exists, define the keep margin first ## Commands ```bash atris experiments init <slug> atris experiments validate atris experiments benchmark ``` ## Good output - short `program.md` - honest `measure.py` - deterministic `loop.py` - append-only `results.tsv` ## Bad output - "felt better" - changed three things at once - kept a patch without a measured win - no reset/revert path