skill-creator

To create and optimize Claude skills, you draft prompts, run structured evaluations with a built-in viewer, compare results, and rewrite based on feedback to improve triggering accuracy and real-world usefulness across multiple iterations.

The best way to evaluate prompt design results is using a built-in eval-viewer pipeline that benchmarks performance, visualizes feedback, and measures triggering accuracy to support iterative skill development and optimization.

Yes, you can bundle scripts, references, and assets as reusable scaffolding to support repeatable skill development, enabling faster deployment and structured workflows across multiple iterations for teams or individuals.

Yes, you need YAML to structure a valid SKILL.md file with frontmatter, which is required for the end-to-end workflow of creating, modifying, and deploying automation skills.

Yes, the skill development workflow supports team collaboration and iteration by allowing multiple users to draft capabilities, run evaluations, compare results, and refine skill descriptions and workflows together.

You should run structured evals before deploying documentation and automation skills to benchmark performance, measure real-world usefulness, and ensure triggering accuracy meets your goals through feedback-driven rewriting.