skill-quality-gate

Evaluates Skill packages for trigger boundaries, output contracts, and regression quality.

3|Updated Feb 13, 2026
One-click install
npx skills add https://github.com/ooooooooooooooooooop/personal-ai --skill skill-quality-gate-ooooooooooooooooooop
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-quality-gate
Source: https://github.com/ooooooooooooooooooop/personal-ai/tree/main/skills/skill-quality-gate
Command: npx skills add https://github.com/ooooooooooooooooooop/personal-ai --skill skill-quality-gate-ooooooooooooooooooop

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve? Reviewing an AI Skill package by intuition alone leads to inconsistent judgments: vague triggers, missing output contracts, and unverified behavior slip through. This Skill provides a structured six-dimension audit (trigger boundaries, workflow, output contract, verification, safety, maintainability) with evidence-based PASS/PARTIAL/BLOCKED verdicts. ## Core Features & Use Cases - Six-Dimension Review: Assesses trigger specificity, workflow ordering, output contracts, verification coverage, safety boundaries, and maintainability, recording facts, inferences, and missing evidence separately. - Deterministic Preflight Script: Runs a standard-library-only Python script that checks frontmatter, section signals, UI metadata, and non-empty examples across one Skill or an entire repository. - Prioritized Findings: Outputs P0/P1/P2 ranked minimal fixes with evidence paths, residual risks, and explicitly out-of-scope items. - Use Case: Before publishing a modified Skill, run the gate to confirm its description states non-applicable scenarios, its examples are non-empty, and its regression checks actually execute. ## Quick Start Use the skill-quality-gate to review the natural-rewrite Skill package and report problems without modifying any files.

Frequently Asked Questions about skill-quality-gate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit an AI Skill package before publishing it?

Run the quality gate review against the target Skill directory, which checks six dimensions: trigger boundaries, workflow, output contract, verification, safety, and maintainability. It returns a PASS, PARTIAL, or BLOCKED verdict with evidence paths and prioritized fixes.

How to run automated quality checks on a Skill repository?

Execute python3 scripts/quality_report.py with --root pointing at the repository and --strict to treat warnings as failures. The script uses only the Python standard library and validates frontmatter, section signals, UI metadata, and non-empty examples.

What does the quality_report.py script check in SKILL.md?

The script verifies YAML frontmatter contains name and description, the file stays under 500 lines, no TODO placeholders remain, and boundary, output, and verification signal sections exist. It also checks agents/openai.yaml fields and non-empty examples.

When should I not use a behavior quality gate for Skills?

Do not use it when you only need structural checks of skills.json, directories, or metadata integrity, which belongs to repository maintenance tooling. It also cannot evaluate a Skill without a target package, examples, or observable outputs.

Can structural validation replace behavioral regression testing for Skills?

No. The structural script only confirms required sections and metadata exist; it cannot prove a Skill behaves correctly on real tasks. Complex Skills still need their own regression tests and pre-release task runs.