unknown-field

YAML frontmatter validation requires parsing the metadata to confirm the required name and description fields are present while safely ignoring extra unknown keys. This approach ensures valid skill discovery without breaking existing repository audit rules.

Extra metadata does not break discovery rules because validation logic preserves required name and description fields while tolerating unknown keys. This allows contributed skills to include custom annotations or internal tracking fields without affecting standard skill ingestion checks.

The best way to audit Skill files for metadata quality is to parse the YAML frontmatter and verify the presence of required fields while flagging nonstandard metadata. This approach helps maintainers assess contributed skills and decide whether extra metadata should be kept or ignored.

Yes, you can use frontmatter validation for repository audits of contributed skills. It checks that Skills remain discoverable by verifying required name and description fields, making it useful for metadata normalization workflows and skill ingestion checks even when custom annotations are present.

To normalize skill metadata without losing custom annotations, parse the YAML frontmatter to confirm required name and description fields are present while tolerating extra keys. This preserves internal tracking data during metadata normalization workflows without breaking discovery rules.