{skill-name}

To standardize YAML frontmatter metadata for AI plugins, you apply a schema defining usage, scope, and prerequisites at the Skill root. This enforces a consistent contract for reliable discovery and activation across units.

The standard schema for documenting AI skill metadata is a machine-readable YAML payload including name, tagline, description, request, complexity, category, keywords, dependencies, components, and toxicity_check fields for downstream indexing.

You extract name and description from a SKILL.md root file by identifying the file and parsing its YAML frontmatter. This validates that the required fields exist to ensure the skill is discoverable.

Yes, you can use optional resource directories like scripts, references, and assets with skill metadata. These directories house supplementary materials alongside the standardized Markdown body that describes operational instructions.

The best way to structure AI plugin documentation for reliable activation is to use a standardized Markdown-based body describing operational instructions, supported by a YAML frontmatter contract enforcing name and description fields.

No, you do not need dependencies to apply a standardized metadata schema for skills. The schema operates independently to extract metadata and produce a YAML payload for indexing without external requirements.