skill-creator

Automate testing for Claude skills by running evaluation loops that measure trigger accuracy and performance across prompts. This generates quantitative results to iterate descriptions and prompts, accelerating reliable skill triggering.

Refine Claude prompts by integrating automated evaluation loops with iteration history. Iterate descriptions and test prompts based on quantitative dashboard results to continuously improve triggering accuracy and task performance.

Yes, you can build and test Claude skills from concept to production-ready prompts. The tool requires YAML dependencies to draft skills, run evaluation loops, and maintain iteration history for continuous improvement.

History-based learning maintains an iteration history of quantitative evaluation results. This allows teams to track improvements over time, iterate descriptions based on past performance, and maximize triggering accuracy.

No, evaluation loops run automatically to measure trigger accuracy and performance across prompts. The tool generates reports and maintains iteration history, enabling continuous improvement without manual testing overhead.