enhanced-skill-creator

To generate a production-ready AI skill scaffold, provide a domain use case to trigger an 8-step workflow that codifies real-world patterns into SKILL.md frontmatter, governance metadata, and structured workflow steps.

Progressive disclosure in skill design structures core rules in SKILL.md while moving dense references, templates, and assets into separate directories for on-demand loading, ensuring deterministic execution without overloading the context budget.

You validate agent skills for routing safety by running self-validating governance checks that evaluate triggers, structure, and readiness, ensuring every created skill passes automated validation before packaging.

The skill creation workflow supports an eval pipeline with train, dev, and holdout sets, performing trigger evaluation and context budgeting alongside governance checks to ensure production readiness.

Yes, you need bash, python3, and git installed in your environment, as these dependencies execute the automated validation scripts, governance checks, and integration operations required for deterministic skill execution.

The limitation of codifying domain patterns into SKILL.md documents is that pattern extraction depends entirely on the quality of provided real-world cases, meaning sparse or ambiguous use cases will yield incomplete governance metadata and workflow scaffolds.