writing-skills

TDD for AI agent skills involves writing failure scenarios first, crafting minimal documentation to pass those tests, and refactoring to close loopholes. This cycle ensures the skill is effective and resistant to misuse.

To prevent AI agents from bypassing skill instructions, use test-driven development to identify failure modes and apply rationalization countermeasures. This methodology refines skill documentation to close loopholes where agents bypass instructions under pressure.

Create a test scenario for AI skill documentation by identifying specific failure modes first. Write minimal documentation to make the scenario pass, then refactor to close loopholes, ensuring the skill effectively enforces the intended agent behavior.

Yes, the test-driven skill creation methodology works for all skill types. It is explicitly applicable to discipline-enforcing, technique, pattern, and reference skills, providing a rigorous framework for refining agent behavior across different categories.

AI skills fail under pressure because agents can rationalize and bypass instructions. The test-driven development methodology addresses this by identifying failure modes early and applying rationalization countermeasures to close documentation loopholes.