What problem does it solve? Writing skill documentation for AI agents without testing it first leads to skills that agents ignore, misinterpret, or rationalize away under pressure. This Skill applies Test-Driven Development to skill authoring so every skill is verified against real agent behavior before deployment. ## Core Features & Use Cases - TDD-based skill authoring: Run baseline pressure scenarios with subagents (RED), write the skill addressing observed failures (GREEN), then close rationalization loopholes (REFACTOR). - Discovery optimization: Guidance on writing description frontmatter with triggering conditions only, keyword coverage, token efficiency, and naming conventions so agents actually find the skill. - Testing methodology: Pressure scenario design (time, sunk cost, authority, exhaustion), rationalization tables, red flag lists, and micro-testing of wording against no-guidance controls. - Use Case: Before publishing a new discipline-enforcing skill like a mandatory code-review rule, run combined-pressure scenarios without the skill, document the agent's verbatim excuses, then write counters for each one and re-test until the agent complies. ## Quick Start Ask the agent to create a new skill following the writing-skills TDD process, starting with a baseline pressure scenario before writing any SKILL.md content.
