skill-creator

To create and evaluate AI skills, draft the SKILL.md file, define deterministic test cases, run performance evaluations, and refine trigger accuracy based on feedback analysis. This iterative workflow supports developing new skills and measuring their performance.

The best way to refine prompt engineering for workflow automation is to run deterministic tests, analyze performance metrics, and iteratively update skill descriptions and logic based on the evaluation results.

You can measure AI skill performance and optimize trigger accuracy by running deterministic tests, analyzing benchmark results, and updating the skill description through iterative development and feedback analysis.

No dependencies are required to build and test new AI tools. The skill development workflow operates independently to draft skills, run evaluations, and iterate on performance using internal scripts and references.

AI skills trigger incorrectly during workflow automation when the description lacks precision. Iteratively optimize trigger accuracy by running deterministic tests, analyzing feedback, and refining the skill description and logic.

To update existing AI skills based on performance evaluation, analyze test results and feedback metrics, then iterate on the skill description and internal logic to optimize code generation and trigger accuracy.