skill-test-designer

Design test scenarios for AI skills by interviewing users and analyzing target skills to generate detailed scenario files covering happy paths and edge cases. This ensures thorough validation and quality assurance before deployment.

Plan quality assurance for test automation by defining task prompts, acceptance criteria, and model choices for each scenario. This approach systematically validates expected usage and potential failure points to ensure reliable skill execution.

Generate edge case scenarios through a user interview by answering questions about your target skill. The process analyzes your input to identify potential failure points and creates specific test coverage alongside standard happy paths.

Create acceptance criteria for skill validation by undergoing an interview process that analyzes your target skill. The resulting scenario files detail specific acceptance criteria and model selections for robust test suite execution.

Test scenario design produces detailed scenario files for execution by a separate skill-tester. This separation ensures the designer focuses purely on scenario generation and planning, while the tester handles the actual validation and execution.

Before deploying a new skill, you need test scenarios covering both expected happy paths and potential edge cases. Generating these scenarios ensures the skill functions reliably across standard usage and handles unexpected inputs safely.