skill-creator

Automating Claude skill creation involves generating a SKILL.md file, running trigger evaluations, and iterating on prompts. This tool applies Claude-based tooling to run end-to-end cycles from draft to improved description.

An evaluation loop for prompt engineering tests skill descriptions against eval-sets, collects results, and iteratively refines prompts. It reduces manual trial-and-error by automating trigger evaluations and producing benchmark reports.

Generating discovery-friendly frontmatter and structure for SKILL.md files requires drafting a solid body that guides activation and usage. This approach automates structuring to speed up skill quality improvements.

Yes, you can use anthropic and yaml dependencies to benchmark Claude skills. The tooling produces evaluation reports, benchmarks, and reviewer-ready notes to inform improvements and stakeholder decisions.

The best way to measure Claude skill performance across multiple evals is running an automated evaluation loop with your eval-set and skill-path. This collects results and produces benchmark reports to optimize descriptions.