skill-creator

Automated prompt engineering iteration runs batched trigger evaluations and benchmarks results, then proposes improvements to descriptions and tests to refine Claude skills. This loop aligns triggering with user intent through repeatable testing.

The best way to structure skill drafting and benchmarking uses an automated lifecycle that captures intent, runs baselines, and generates SKILL.md content with bundled scripts. This produces structured, triggerable skills with clear documentation.

Yes, running batched trigger evaluations and quality checks requires installing anthropic and pyyaml dependencies. These libraries enable the evaluation scripts to validate skill structures and execute automated testing workflows.

Yes, you can use this workflow to generate structured SKILL.md documentation and manage references, assets, and optional bundled scripts. It organizes multi-stage workflows to ensure clear documentation and quality validation before deployment.

An iterative improvement loop for skill creation codifies the entire lifecycle into a repeatable process, unlike manual prompt testing. It automatically proposes improvements and re-runs evaluations to ensure reliable triggering and robust quality checks.

Automating skill refinement with batched trigger evaluations requires structured evals and references to function correctly. Limitations include the need for precise test prompt design and dependency management to avoid misaligned automated improvements.