labautoresearch

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Self-improving loop for plugin skills. Reads program.md, proposes one mutation per iteration, evaluates against deterministic scorer, keeps improvements via git, reverts failures. Targets weakest skill+dimension. Use with /loop for overnight runs.

AI & Automation 243 stars 17 forks Updated 1 months ago MIT

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Skill Content

# Autoresearch — Plugin Skill Self-Improvement Iteratively improve plugin skills via the autoresearch pattern: propose one mutation -> eval -> keep/revert -> repeat. ## Usage ``` /lab:autoresearch # Targeted: attack weakest skill+dimension /lab:autoresearch --skill review # Focus on one skill /lab:autoresearch --strategy sweep # Process all skills alphabetically /lab:autoresearch --dry-run # Show what would change, don't commit ``` For overnight runs: ``` /loop 5m /lab:autoresearch --strategy sweep --max-iterations 200 ``` ## Iron Laws 1. **ONE mutation per iteration** — if description needs "and", split into two 2. **NEVER mutate read-only files** — check program.md before every write 3. **EVAL is deterministic** — always use the wrapper script, never LLM-judge 4. **REVERT on regression OR checks failure** — no exceptions 5. **LOG every iteration** — use `keep` or `revert` command (never skip) 6. **CHECK ideas.md before proposing** — don't rediscover known optimizations ## Wrapper Script Commands All eval/git/journal operations go through ONE script. Do NOT run these manually. ```bash # Find the weakest skill+dimension python3 lab/autoresearch/scripts/run-iteration.py target --strategy targeted # Score a skill (before mutation, to get baseline) python3 lab/autoresearch/scripts/run-iteration.py score <skill-name> # After mutation: score + checks + compare → verdict (KEEP or REVERT) python3 lab/autoresea...

Details

Author
oliver-kriska
Repository
oliver-kriska/claude-elixir-phoenix
Created
3 months ago
Last Updated
1 months ago
Language
Python
License
MIT

Integrates with

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