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Auto-optimize skills through mutate-verify loops. Use when skill tests show failures or when asked to optimize a skill.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
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Closure reflection protocol. After a significant work block concludes (feature shipped, session ending, major commit landed, cross-node coordination resolved), runs a 10-question interview that extracts meaning, impact, and next questions — then emits multiple audience-specific artifacts (changelog, external editorial, AI integration docs, memory crystal, backlog seed). Turns implicit maturation into explicit narrative. Use at the end of meaningful work, not after trivial edits.
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| name | autoresearch |
| description | Auto-optimize skills through mutate-verify loops. Use when skill tests show failures or when asked to optimize a skill. |
| user-invocable | true |
The system improves its own skills through iterative loops.
Run /eval on the target skill. Record trigger accuracy and fidelity.
For each failure:
ONE change per iteration. Never more than one variable at a time.
Run /eval again. Compare with baseline:
Baseline → final score, what changed, how many iterations.
