---
name: skill-optimizer-019de9dea8f6
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


---
Source attribution: mcollina
Original project: https://github.com/mcollina/skills/blob/c75d70dbfbe991d8cec42aeda0b64ff14fbb9ac7/skills/skill-optimizer/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Matteo Collina

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: mcollina
Original project: https://github.com/mcollina/skills/blob/c75d70dbfbe991d8cec42aeda0b64ff14fbb9ac7/skills/skill-optimizer/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Marketing, Product Management
Roles: Data Analyst, Growth Marketer, Marketing Analyst, Product Manager, Technical Product Manager
Specialties: Specialty not specified
Tools: Tool not specified
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: e3e0e5aa66e7c584b58c26b7edc78de95f9d8b06f707afb6d3d6620593a70b6a