skill-creator

To create AI skills, you define the intent, write the SKILL.md file, bundle resources, and run evaluations. This process supports iterative refinement through automated testing and feedback loops to optimize skill descriptions and accuracy.

The best way to refine prompt engineering descriptions is through automated evaluation and iterative development. You run test cases, analyze the results, and automatically tune the skill descriptions to ensure optimal triggering accuracy.

Yes, you can use iterative development to improve AI skill creation. The workflow guides you through running evaluations, analyzing feedback loops, and refining the SKILL.md and bundled resources until the desired performance is achieved.

Yes, writing a SKILL.md file is required to bundle resources for AI development. It acts as the core configuration where you define the skill's intent, structure the automated testing evaluations, and manage iterative refinement.

Modifying AI skills through automated testing relies heavily on the quality of your initial test cases and defined intent. If the evaluation criteria are poorly structured, the iterative refinement feedback loops will not effectively optimize the description triggering accuracy.