craft-skill

To use TDD for AI agent skills, you first write a failing test scenario proving the skill's necessity, then create the skill to pass that scenario, and finally refactor to close loopholes. This RED-GREEN-REFACTOR cycle ensures robust agent behavior.

AI agents bypass skill instructions under pressure by rationalizing around procedural rules. You can prevent this by applying TDD to skill development, which uses pressure scenarios to identify and close loopholes before finalizing the instructions.

The best way to document AI agent skills effectively is to enforce Test-Driven Development principles. By requiring a failing test scenario before skill creation, you ensure the documentation directly addresses specific operational bypasses and procedural rules.

To bulletproof skill instructions against agent rationalizations, you iteratively test against new pressure scenarios after the initial skill creation. This refactoring phase ensures strict compliance by identifying and closing loopholes where agents might bypass guidelines.

Yes, you can use TDD principles for refactoring existing AI agent skills. By writing new pressure scenarios to see how agents bypass current guidelines, you can iteratively refine the skill to ensure strict compliance under pressure and improve documentation.

You need test-driven development for skill creation when solving the problem of poorly documented or ineffective AI agent skills. It enforces procedural compliance by requiring a failing test scenario before skill creation to prove its necessity.