skill-creator

To create and iterate on Claude Skills, use a structured workflow to draft SKILL.md instructions, define test prompts, run evaluation loops, and refine triggers based on benchmark feedback.

The best way to evaluate skill performance is running multi-step evaluation loops with train/test splits, comparing configurations, and tracking progress over iterations to systematically improve instructions.

You package skills for distribution by validating instructions, benchmarking performance against test prompts, and preparing progressive disclosure content including assets and references for deployment.

Yes, you can test trigger conditions by defining specific test prompts within the evaluation workflow to validate when your SKILL.md instructions activate and how accurately they respond.

Yes, you need YAML and Anthropic dependencies installed to support the evaluation workflow, manage configuration files, and execute the iterative benchmarking loops for your skills.

Progressive disclosure is needed to manage complexity by structuring SKILL.md content so Claude receives relevant instructions and references contextually, improving evaluation accuracy and reducing token overload.