skill-creator

To benchmark and iterate on skills, this tool coordinates interview prompts, evaluation loops, and benchmark analysis to surface actionable insights, enforcing a deterministic workflow for skill creation, testing, iteration, and packaging.

The best way to coordinate the skill lifecycle is to write a SKILL.md, assemble an eval_set, run parallel evals, review the benchmark, and decide the best iteration using the dashboard to reduce subjective guesswork.

Yes, you can compare multiple skill versions, including vanilla baselines, to produce decision briefs that automate the end-to-end process of creating, iterating on, and benchmarking skills.

Yes, the anthropic dependency is required to run the evaluation loops and orchestration artifacts that generate SKILL.md content and enforce the deterministic workflow for testing and packaging skills.

Manual skill testing lacks a structured workflow, whereas automating the end-to-end process of creation, iteration, and benchmarking enforces deterministic evaluation loops that surface actionable insights for evidence-based decisions.

A deterministic workflow for skill benchmarking enforces a strict process for SKILL.md generation and evaluation loops, which may reduce subjective guesswork but requires assembling a proper eval_set to run parallel evals effectively.