skill-authoring

# Skill Authoring Guide

## Overview

Writing effective Claude Code skills requires Test-Driven Development (TDD) and persuasion principles from compliance research. We treat skill writing as process documentation that needs empirical validation rather than just theoretical instruction. Skills are behavioral interventions designed to change model behavior in measurable ways.

By using TDD, we ensure skills address actual failure modes identified through testing. Optimized descriptions improve discovery, while a modular structure supports progressive disclosure to manage token usage. This framework also includes anti-rationalization patterns to prevent the assistant from bypassing requirements.

### The Iron Law

**NO SKILL WITHOUT A FAILING TEST FIRST**

Every skill must begin with documented evidence of Claude failing without it. This validates that you are solving a real problem. No implementation should proceed without a failing test, and no completion claim should be accepted without evidence. Detailed enforcement patterns for adversarial verification and coverage gates are available in `imbue:proof-of-work`.

## Skill Types

We categorize skills into three types: **Technique** skills for specific methods, **Pattern** skills for recurring solutions, and **Reference** skills for quick lookups and checklists. This helps organize interventions into the most effective format for the task.

## Quick Start

### Skill Analysis
\`\`\`bash
# Analyze skill complexity
python scripts/analyze.py

# Estimate tokens
python scripts/tokens.py
\`\`\`

### Validation
\`\`\`bash
# Validate skill structure
python scripts/abstract_validator.py --check
\`\`\`

**Verification**: Run analysis and review token estimates before proceeding.
## Description Optimization

Skill descriptions must be optimized for semantic search and explicit triggering. Follow the formula `[What it does] + [When to use it] + [Key triggers]`. Use a third-person voice (e.g., "Guides...", "Provides...") and inclu