frontmatter-validation

YAML frontmatter validation scans an entire Markdown repository to check required fields like name, description, and last_updated. It performs batch validation on all files, enforcing consistent schemas and generating a report of any inconsistencies found.

Yes, you can automatically fix missing metadata and stale values in Markdown documentation. The validation process auto-fixes common frontmatter issues by inferring correct metadata from file paths and applying a consistent schema across the repository.

Valid YAML frontmatter requires specific fields: name, description, token_estimate, last_updated, and status. The validator checks that these required fields are present, validates their data types, and ensures the values match the expected schema.

The best way to ensure consistent metadata across a large documentation repository is batch validation. This process scans multiple Markdown files, enforces required frontmatter fields, validates data types, and automatically applies standardized schemas to maintain consistency.

Frontmatter validation works with both standard Markdown documentation files and SKILL.md entries. It targets large repositories containing multiple documentation formats, applying consistent schemas and validating required metadata fields across all file types.