writing-skills

To use TDD for AI skill development, you write failing test scenarios first, create minimal skills to pass those tests, and refactor to close loopholes. This RED-GREEN-REFACTOR cycle ensures skills are robust and compliant.

Pressure scenario testing simulates real-world constraints like time, sunk cost, and authority to test AI skill compliance. It ensures agents adhere to rules even under tight deadlines or conflicting priorities in agentic workflows.

AI agents bypass rules by finding loopholes in skill documentation to rationalize non-compliance. You prevent rationalizations by explicitly addressing and closing these loopholes during the refactoring phase of test-driven skill development.

Refactor skill documentation by closing loopholes agents use to bypass rules, ensuring explicit compliance standards. This test-driven refactoring improves skill discoverability and effectiveness in agentic workflows.

Yes, you can apply test-driven development to documentation for code review skills. Write failing test scenarios under pressure constraints first, then develop the minimal skill, ensuring agents adhere to review standards even under tight deadlines.

A limitation of using TDD for skill creation is the need to anticipate rationalizations and pressure scenarios accurately. If failing test scenarios do not simulate real-world constraints properly, agents may still bypass the intended rules.