skill-creator

To create agent skills, you design structured instructions and metadata, then validate YAML frontmatter and required fields using bundled scripts. This ensures skills are self-contained with proper resource directories and hyphen-case naming.

Validating metadata consistency involves checking naming conventions, YAML frontmatter, and required fields using PyYAML-based scripts. This process ensures skill structures trigger correctly before forward-testing realistic tasks.

Yes, PyYAML is a required dependency for running the bundled validation and metadata scripts. It parses YAML frontmatter to verify required fields and metadata consistency during skill creation.

Updating existing skills involves revising structured instructions, metadata, and resources to improve triggering. You validate the updated YAML frontmatter and workflow specialization before forward-testing execution quality.

Tool integration within skills requires self-contained resource directories and valid metadata. Limitations arise when workflows omit required frontmatter or lack populated resource folders, preventing proper validation.

Resource directories must be populated when skills require reusable resources like scripts or references. This ensures the skill remains self-contained and functions correctly during agent workflow execution.