writing-skills

Test agent documentation by applying Test-Driven Development principles to skill creation. Write pressure scenarios that expose agent failures before writing the Skill documentation, ensuring instructions guide behavior effectively under stress.

Test-Driven Development for AI agent skills is a methodology enforcing a strict RED-GREEN-REFACTOR cycle. It requires creating failing pressure scenarios first, then writing or refining documentation to make the agent pass those tests and close loopholes.

AI agents ignore instructions when documentation lacks rigorous testing against edge cases. Using a TDD approach for documentation closes loopholes by iteratively refactoring instructions based on specific agent failures observed during pressure scenarios.

Refine skill documentation by iteratively refactoring it based on agent failures. Continuously verify instructions against agent rationalizations during pressure scenarios to close loopholes and improve clarity for better compliance.

Yes, you can use TDD for iterative improvement of existing agent behaviors. The methodology applies to the entire skill lifecycle, allowing you to refactor existing instructions under pressure by continuously verifying them against new failing scenarios.