# Eval Optimize

> Automated skill improvement loop. Runs eval, identifies judge failures, reads traces and rationale, edits the SKILL.md to fix issues, re-runs to verify, and checks for regressions. Use when the user wants to automatically improve a skill based on eval results, fix failing judges, make the skill better, auto-fix quality issues, improve scores, or iterate until all judges pass. Triggers on "optimize the skill", "make it pass", "auto-fix", "improve the scores", "why is it failing". Works best after /eval-run has produced results to learn from.

## Facts
- Page: https://tashan.sh/capability/skill-opendatahub-io-eval-optimize
- tashan id: skill:opendatahub-io/eval-optimize
- Source: https://github.com/opendatahub-io/agent-eval-harness
- Type: skill
- Category: other
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 97.0
- Freshness: 94.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: Apache-2.0
- Official: no

## Install

```sh
cp -r eval-optimize ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

---
Measured 2026-09-12 by tashan (https://tashan.sh) from public evidence. Scorer s5.