Applies Test-Driven Development principles to create high-quality, discoverable AI skills and process documentation.
This skill provides a rigorous framework for developing AI capabilities using a specialized Red-Green-Refactor cycle adapted for documentation. It ensures that every skill created actually improves AI performance by requiring developers to verify baseline failures before implementation. The guide covers Claude Search Optimization (CSO), token-efficient writing patterns, and strict metadata standards to ensure skills are discoverable and correctly interpreted by AI agents without consuming unnecessary context.
주요 기능
01Claude Search Optimization (CSO) for better skill discovery
02TDD-based documentation workflow (Red-Green-Refactor for skills)
03Pressure-testing methodology for verifying agent compliance
04Standardized SKILL.md structure and YAML frontmatter templates
051 GitHub stars
06Token-efficient documentation patterns and compression techniques
사용 사례
01Standardizing internal development workflows for AI-assisted engineering teams
02Debugging and refactoring existing AI prompts and skills to reduce context leakage
03Creating reusable technical reference guides that agents can find and follow autonomously