writing-skills

TDD for AI agent skills involves applying a RED-GREEN-REFACTOR cycle to skill documentation and testing methodologies. You first write a failing test scenario demonstrating a current violation, then create the skill to pass it, and finally refactor the documentation.

Pressure testing for skill compliance involves developing and running scenarios with multiple pressures, such as time, sunk cost, and authority, to test if an AI skill maintains its rules. It ensures the agent adheres to standards even under simulated stress.

To stop AI agents from rationalizing and bypassing rules, implement rationalization countermeasures within your skill. This identifies common excuses agents use to skip protocols and explicitly addresses them in the skill documentation to enforce strict compliance.

You should apply test-driven development to skill documentation when creating a new skill to enforce critical coding standards. It is necessary when you need to ensure the skill is robust, effective, and compliant under pressure before deployment.

The best way to ensure AI skills are robust and effective is to enforce Test-Driven Development principles during creation. This approach requires adherence to specific testing protocols and pressure scenario development to verify the skill holds up under stress.