Implements a Test-Driven Development approach to creating, verifying, and optimizing Claude Code skills for maximum reliability.
TDD Skill Authoring applies the rigorous Red-Green-Refactor cycle to the process of writing AI documentation. Instead of writing instructions based on assumptions, this skill guides authors to create pressure scenarios with subagents to verify baseline failures, ensuring that every line of a new skill is necessary and effective. By focusing on Claude Search Optimization (CSO) and token efficiency, it helps developers build a high-performance library of reusable techniques and patterns that Claude can easily discover and execute without rationalization or context bloat.
Key Features
01Claude Search Optimization (CSO) patterns
02Red-Green-Refactor workflow for documentation
03Standardized SKILL.md template generation
044 GitHub stars
05Subagent pressure testing and verification
06Token-efficient documentation structures
Use Cases
01Optimizing existing prompt libraries for context window efficiency
02Creating reusable technical patterns for team-wide AI workflows
03Verifying that new documentation effectively changes AI agent behavior