skill-creator

To create and benchmark Claude skills, you draft SKILL.md frontmatter, run trigger evaluations, compare against baselines, and generate quantitative benchmarks to drive iterative improvements. This workflow applies automation scripts and testing harnesses to measure quality across iterations.

Evaluating skill triggering and measuring quality involves running automated trigger evaluations and comparing results against baselines. You generate quantitative benchmarks to track progress, utilizing testing harnesses and a viewer ecosystem to visualize results and refine skill descriptions deterministically.

To modify and improve existing skills, you run an end-to-end evaluation and improvement loop that refines descriptions and tests triggering. Automation scripts optimize skill descriptions, package skills, and generate reports to iterate from draft to production-ready status.

Yes, you need the pyyaml dependency to define SKILL.md frontmatter and author skill descriptions. This dependency supports the structured workflow required to manage multi-step instructions that load deterministically and enable the end-to-end iteration process.

Yes, you can automate skill packaging and visualize evaluation results in a viewer. The skill creator provides automation scripts to generate reports, package skills, and an eval viewer ecosystem that enables end-to-end iteration from draft to production-ready skill descriptions.

Benchmarking skill performance across iterations relies on quantitative benchmarks and trigger evaluations compared against baselines. Limitations include the need for a structured SKILL.md frontmatter and the requirement to run deterministic testing harnesses to ensure measurable progress and accurate quality measurements.