writing-skills

To use TDD for AI agent skills, apply the RED-GREEN-REFACTOR cycle to skill documentation by writing pressure scenarios first, then refining the documentation to pass those tests. This ensures agent behaviors remain compliant and robust against rationalization.

Pressure scenarios in agent testing are realistic situations designed to test AI compliance under stress. They are needed to verify that agents follow skill rules strictly, even when simulating constraints like time pressure, preventing rationalization or skipped steps.

To prevent AI agents from rationalizing and bypassing skill documentation, document agent failures during pressure tests and refactor the documentation to explicitly close loopholes. This countermeasure strategy eliminates common excuses for non-compliance.

The best way to document agent failures during skill development is to record the agent's rationalizations when it fails a pressure scenario. Use these documented failures to write minimal skill documentation updates that directly counter the bypassed rules.

Yes, you can apply test-driven development to existing AI agent documentation by using the refactoring phase. Write new pressure scenarios to expose compliance loopholes, then edit the existing skill documentation to pass these tests and close rationalization gaps.

Use test-driven skill development instead of standard documentation when robust agent compliance is critical. It is necessary when agents face high-stress scenarios where they might rationalize bypassing rules, requiring pressure testing to verify strict adherence.