skill-judge

Evaluate AI Agent Skills against official specifications with multi-dimensional scoring.

Updated Mar 16, 2026
One-click install
npx skills add https://github.com/Likas07/t3code-skills --skill skill-judge-likas07
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-judge
Source: https://github.com/Likas07/t3code-skills/tree/main/skills/skill-judge
Command: npx skills add https://github.com/Likas07/t3code-skills --skill skill-judge-likas07

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a rigorous, multi-dimensional framework for evaluating the quality, effectiveness, and adherence to best practices of AI Agent Skills, ensuring they deliver maximum value and efficiency.

Core Features & Use Cases

  • Objective Scoring: Assigns scores across 8 critical dimensions (Knowledge Delta, Mindset, Anti-Patterns, etc.) totaling 120 points.
  • Actionable Feedback: Identifies specific areas for improvement with concrete suggestions.
  • Use Case: When reviewing a newly developed Skill for a complex task like code generation, use this Skill to objectively assess its design, identify potential token waste, and ensure its description is optimized for agent activation.

Quick Start

Evaluate the quality of the 'skill-judge' Skill using the provided SKILL.md file.

Frequently Asked Questions about skill-judge

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

FAQPage Schema
How do I evaluate the design quality of AI agent skills?

Evaluating AI agent skills involves scoring their design against official specifications and best practices across 8 dimensions. This process identifies token waste and ensures descriptions are optimized for agent activation, providing actionable improvement suggestions.

What is the best way to audit a SKILL.md file for prompt engineering best practices?

Auditing a SKILL.md file requires applying a defined evaluation protocol and scoring rubric. This objective assessment scores critical dimensions like Knowledge Delta and Anti-Patterns, totaling 120 points, to ensure maximum value and efficiency.

Can I use a standardized rubric to review complex skill packages?

Yes, you can review entire skill packages by applying a multi-dimensional scoring framework. This approach objectively assesses complex tasks like code generation skills, identifying potential issues and verifying adherence to defined quality assurance protocols.

Does skill evaluation automatically identify token waste in AI agents?

Skill evaluation identifies potential token waste by assessing the design quality and effectiveness of AI agent skills. The objective scoring highlights specific areas for improvement, ensuring the skill description is optimized for efficient agent activation.

What dimensions are scored when reviewing AI agent skills?

Reviewing AI agent skills assigns scores across 8 critical dimensions, including Knowledge Delta, Mindset, and Anti-Patterns, totaling 120 points. This multi-dimensional framework ensures skills deliver maximum value and adhere to best practices.