skill-review

Audit AI agent skills for structural compliance and token efficiency.

Updated May 15, 2026

Search Tags:#workflow #optimization #audit #quality #skill #lint

Ready to run

npx skills add https://github.com/j-show/ai-everything --skill skill-review-j-show

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-review
Source: https://github.com/j-show/ai-everything/tree/main/skills/skill-review
Command: npx skills add https://github.com/j-show/ai-everything --skill skill-review-j-show

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the lack of systematic quality control for AI agent skills, preventing issues like vague instructions, bloated context, and ineffective workflows.

Core Features & Use Cases

Five-Dimensional Audit: Evaluates structure, description quality, workflow design, token efficiency, and anti-patterns.
Actionable Reporting: Provides prioritized, specific fixes rather than generic feedback.
Use Case: Use this before publishing a new skill to ensure it follows best practices and provides a reliable, high-quality experience for end users.

Quick Start

Run the skill review command on your target skill directory to receive a prioritized report of improvements.

Frequently Asked Questions about skill-review

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

FAQPage Schema

How do I audit AI agent skills for structural compliance and token efficiency?▼

To audit AI agent skills, you can run a five-dimensional review that evaluates structural compliance, description quality, workflow design, token efficiency, and anti-patterns to ensure high-quality model outputs.

What is the best way to prevent vague instructions and bloated context in agent workflows?▼

Preventing vague instructions and bloated context requires systematic quality control that validates skill metadata, instruction clarity, and adherence to established anti-pattern guardrails before publishing.

How do I check if my plugin-based agent toolkit follows established anti-pattern guardrails?▼

You can check your plugin-based agent toolkit by running an automated audit that validates skill metadata and verifies adherence to established anti-pattern guardrails for structural compliance.

Does the skill review process provide specific fixes for workflow design issues?▼

Yes, the skill review process provides actionable reporting with prioritized, specific fixes rather than generic feedback when it identifies workflow design or structural issues.

When do I need to run a token efficiency audit on my agent skills?▼

You need to run a token efficiency audit before publishing a new skill to ensure it follows best practices and provides a reliable, high-quality experience without bloated context.

What specific dimensions are evaluated during an AI agent skill quality audit?▼

An AI agent skill quality audit evaluates five dimensions: structure, description quality, workflow design, token efficiency, and adherence to anti-patterns to ensure actionable outputs.