advanced-example

Skill metadata includes required fields like name, category, keywords, dependencies, and components organized in a structured YAML format. This Skill demonstrates every available metadata field with a working reference implementation, ensuring your skills are discoverable and functional.

Organize skills with a root directory containing SKILL.md metadata, plus subdirectories for examples/ and templates/ for better maintainability. This structure supports Python and system dependencies like pydantic, aiofiles, git, and curl while enabling hot-reload updates.

Validation enforces required fields, YAML syntax correctness, folder structure adherence, and file references. This Skill automates metadata creation and validation to catch disorganized or incomplete metadata early, ensuring accurate categorization and tagging for discovery.

Yes, skill metadata supports explicit dependency tracking for both Python packages and system tools, plus versioning and template management. This enables precise environment reproduction and helps users understand prerequisites before using your skill.

Document use cases within comprehensive metadata fields and provide working examples in dedicated subdirectories. This Skill shows how to capture all relevant information—from usage scenarios to implementation depth—so users can quickly understand when and how to apply your skill.