skill-creator

Automating Claude Skills workflows involves capturing initial intent, drafting SKILL.md files, running evals, and refining descriptions iteratively. Local scripts orchestrate the process from generation through evaluation to report creation.

Evaluating and improving a SKILL.md file uses a run_loop script to execute eval cycles and generate reports. You iteratively refine the skill description based on benchmark results until it meets performance targets.

Packaging reusable skills as .skill files bundles your SKILL.md content, associated scripts, and reference assets together. This creates a single distributable archive for deployment across different environments.

Yes, running skill evaluation cycles requires Python with the anthropic and pyyaml dependencies installed. These libraries support the local scripts that execute evals, generate reports, and manage the iteration loop.

The skill-creator automation workflow includes local scripts for generate_report, run_eval, run_loop, and improve_description. These components manage the structured creation, testing, evaluation, and refinement of skills.

Using local scripts for skill evaluation requires a controllable local environment and limits distributed testing. All eval cycles, report generation, and improvement loops depend on these specific scripts running within your local setup.