# Optimize · scaledown-team

> Optimize the prompt you pass to a ScaleDown SLM (extract, classify, summarize, or compress) and benchmark it against a baseline — the frontier-model output it replaced, or your ground truth — on the user's own data. Collects sample data and a ScaleDown API key; if the user has no samples, walks them through creating and validating a small labeled set first. Then runs repeatable evals with a metric appropriate to the task type, quantifies run-to-run noise, and iterates the prompt until it beats — or matches within noise — the baseline. General by design: adapts to any use case, with task-specific playbooks.

## Facts
- Page: https://tashan.sh/capability/skill-scaledown-team-optimize
- tashan id: skill:scaledown-team/optimize
- Source: https://github.com/scaledown-team/SLM_Agent
- Type: skill
- Category: ai
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 95.0
- Freshness: 89.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- Official: no

## Install

```sh
cp -r 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.

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Measured 2026-08-23 by tashan (https://tashan.sh) from public evidence. Scorer s5.