Skill Judge

Evaluate Agent Skills against official specifications and patterns derived from 17+ official examples.

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Core Philosophy

What is a Skill?

A Skill is NOT a tutorial. A Skill is a knowledge externalization mechanism.

Traditional AI knowledge is locked in model parameters. To teach new capabilities:

Traditional: Collect data → GPU cluster → Train → Deploy new version
Cost: $10,000 - $1,000,000+
Timeline: Weeks to months

Skills change this:

Skill: Edit SKILL.md → Save → Takes effect on next invocation
Cost: $0
Timeline: Instant

This is the paradigm shift from "training AI" to "educating AI", like a hot-swappable LoRA adapter that requires no training. You edit a Markdown file in natural language, and the model's behavior changes.

The Core Formula

Good Skill = Expert-only Knowledge − What the Base Model Already Knows

A Skill's value is measured by its knowledge delta, the gap between what it provides and what the model already knows.

• Expert-only knowledge: Decision trees, trade-offs, edge cases, anti-patterns, domain-specific thinking frameworks, things that take years of experience to accumulate
• What the base model already knows: Basic concepts, standard library usage, common programming patterns, general best practices

When a Skill explains "what is PDF" or "how to write a for-loop", it's compressing knowledge the base model already has. This is token waste, context window is a public resource shared with system prompts, conversation history, other Skills, and user requests.

Tool vs Skill

Concept	Essence	Function	Example
Tool	What model CAN do	Execute actions	bash, read_file, write_file, WebSearch
Skill	What model KNOWS how to do	Guide decisions	PDF processing, MCP building, frontend design