writing-skills

Test-Driven Development for agent skills documentation applies a structured RED-GREEN-REFACTOR cycle to author and verify instructions. It enforces baseline testing and pressure scenario validation to ensure agent compliance before deployment.

Pressure testing for AI agents validates skill instructions against real-world constraints like time, authority limits, and exhaustion. You need it to close loopholes and prevent agent rationalizations when operating under high-stress conditions.

To stop AI agents from rationalizing, you implement explicit anti-rationalization patterns during the skill authoring process. Structured TDD frameworks enforce these patterns by validating behaviors against pressure scenarios before deployment.

Yes, you can use TDD to verify process improvement for existing agent capabilities by defining a failing pressure scenario and documenting the required behavior. This ensures updates are validated against real-world constraints.

No, writing-skills does not require external testing dependencies to validate documentation. It operates independently using internal scripts to facilitate the RED-GREEN-REFACTOR cycles and pressure scenario validation.

A limitation of using TDD for quality assurance in agent documentation is that it requires defining explicit pressure scenarios upfront. Without accurately anticipating real-world constraints, baseline testing may not cover all edge cases.