skill-judge

# Skill Judge

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

---

## 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 Claude 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 Claude 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 Claude 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 |

Tools define capability boundaries — without bash tool, model can't execute commands.
Skills inject knowledge — without frontend-