customaize-agent-create-skill

To create AI skills using TDD, you define failure scenarios first (RED), write the skill documentation to pass those scenarios (GREEN), and iteratively refine it to close loopholes (REFACTOR). This ensures robust agent behavior and prevents AI rationalization.

AI agents rationalize and ignore skill documentation when instructions lack strict constraints. Applying a TDD methodology to skill creation bulletproofs the documentation by testing subagents with failure scenarios and refining instructions to close loopholes.

The best way to optimize AI skill naming conventions and keywords is to treat skills as documentation and iteratively test them with subagents. This TDD approach ensures token efficiency and precise agent behavior alignment.

Yes, you can apply the RED-GREEN-REFACTOR cycle to prompt engineering by writing tests for agent behavior first. This TDD methodology verifies agent responses, ensuring documentation effectively enforces compliance and prevents rationalization.

To bulletproof AI skills and prevent rationalization, you iteratively test them with subagents to identify behavioral loopholes. You then refactor the skill documentation to enforce strict compliance and close those specific failure scenarios.