Applies Test-Driven Development principles to creating, verifying, and refining documentation and skills for AI agents.
This skill adapts the Red-Green-Refactor cycle of TDD to the process of writing AI instructions and skills. By forcing authors to watch an agent fail a pressure scenario before writing the documentation, it ensures that every instruction is necessary, effective, and resilient against agent rationalizations. It provides a structured framework for creating high-performance, token-efficient skills that Claude can reliably discover and execute across different projects.
主な機能
01Claude Search Optimization (CSO) guidelines
02Red-Green-Refactor workflow for documentation
030 GitHub stars
04Token-efficient documentation patterns
05Standardized SKILL.md structure
06Subagent pressure-testing framework
ユースケース
01Optimizing documentation for AI discoverability and context efficiency
02Refining existing instructions to prevent agent hallucinations