What problem does it solve? Writing documentation-style skills for AI agents often produces untested instructions that agents ignore or rationalize away under pressure, leading to unreliable behavior in production. ## Core Features & Use Cases - TDD for Skills: Applies the RED-GREEN-REFACTOR cycle to skill authoring—run baseline pressure scenarios without the skill, document agent failures verbatim, then write the skill to address those specific rationalizations. - Discovery Optimization (CSO): Guidelines for writing descriptions, keywords, and names so future agents can find and correctly trigger the skill. - Bulletproofing Techniques: Rationalization tables, red flag lists, and persuasion principles to close loopholes in discipline-enforcing skills. - Use Case: Before deploying a new TDD-enforcement skill, run pressure scenarios (time pressure + sunk cost + exhaustion) with subagents, capture their excuses, and iteratively harden the skill until agents comply under maximum pressure. ## Quick Start Ask the agent to help you create a new skill by first running a baseline pressure scenario with a subagent, then drafting the SKILL.md based on the observed failures.
