What problem does it solve? Writing skills for AI agents without testing them first leads to documentation that agents ignore or rationalize away under pressure. This Skill applies test-driven development to skill authoring, ensuring every skill is validated against real baseline failures before deployment. ## Core Features & Use Cases - TDD-Based Skill Authoring: Enforces a RED-GREEN-REFACTOR cycle where pressure scenarios are run with subagents before any skill content is written. - Loophole Closing: Provides systematic techniques for capturing agent rationalizations verbatim and adding explicit counters, red flags lists, and rationalization tables. - Frontmatter and Structure Guidance: Defines naming rules, description requirements (what + when, third person, under 1024 characters), degrees-of-freedom calibration, and progressive disclosure patterns. - Use Case: When creating a new discipline-enforcing skill like a TDD requirement, run baseline pressure scenarios with subagents first, document their excuses, then write a skill that specifically counters those observed failures and re-test until bulletproof. ## Quick Start Use the make-skill skill to create a new agent skill following the test-driven development workflow with baseline pressure testing.