skill-optimizer

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 3f067ed6a979 · 28 Oct 2026Report an issue or request a re-scan

• Publishermcollina GitHub userOwner of the repository this skill is read from
• Source foldermcollina/skills/skills/skill-optimizerThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict3f067ed6a979A new audit runs when the source changes
• Repository statusNot archivedPushed today
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Optimizes AI skills for activation, clarity, and cross-model reliability. Use when creating or editing skill packs, diagnosing weak skill uptake, reducing regressions, tuning instruction salience, improving examples,…

---
name: skill-optimizer
description: "Optimizes AI skills for activation, clarity, and cross-model reliability. Use when creating or editing skill packs, diagnosing weak skill uptake, reducing regressions, tuning instruction salience, improving examples, shrinking context cost, or setting benchmark/release gates for skills. Trigger terms: skill optimization, activation gap, benchmark skill, with/without skill delta, regression, context budget, prompt salience."
metadata:
  tags: skills, optimization, benchmarking, activation, regressions, prompt-engineering
---

## When to use

Use this skill when you need to:
- Improve whether a skill is actually applied by models
- Diagnose why some criteria fail across all models
- Prevent a skill from making outputs worse
- Refactor skill text for stronger retrieval under context pressure
- Build repeatable benchmark loops and release gates

## Optimization loop (default workflow)

1. **Measure baseline and skill-on behavior** (per model, per scenario, per criterion)
2. **Find failure pattern**:
   - universal failure (0% with skill)
   - model-specific weakness
   - regression (negative delta)
3. **Edit for salience**:
   - add explicit triggers
   - add concrete integrated examples
   - tighten checklists and decision rules
4. **Re-run evals** and compare deltas
5. **Ship with guardrails** (documented gate + run history + follow-up issues)

## How to use

Read individual rule files for detailed procedures and templates:

- [rules/benchmark-loop.md](rules/benchmark-loop.md) - End-to-end benchmark loop and scoring
- [rules/activation-design.md](rules/activation-design.md) - Improve retrieval and instruction uptake
- [rules/context-budget.md](rules/context-budget.md) - Reduce token cost without losing behavior
- [rules/regression-triage.md](rules/regression-triage.md) - Diagnose and fix skill-on regressions
- [rules/release-gates.md](rules/release-gates.md) - Go/no-go criteria before shipping skill updates

## Practical heuristics

- Prefer **few high-signal rules** over many soft recommendations
- Put fragile, high-value behaviors in **top-level checklists**
- Include at least one **integrated example** per common scenario
- Add explicit wording for what must **not** be omitted
- Track gains/losses with **with-skill vs without-skill** comparisons

Excerpt, first 2,326 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/mcollina/skills
git -C skills checkout 3f067ed6a979

Works in

1. 2026-10-28
   ✓SAFE B 89 / 100

   first audit · source 3f067ed6a979

Questions about skill-optimizer

• github.com/mcollina/skills/tree/main/skills/skill-optimizer — the audited source at commit 3f067ed6a979 and every finding aboveObserved · 28 Oct 2026

Spotted something wrong? Report a correction · Methodology