nested-mid-skill

Deeply nested directory discovery automatically traverses multi-level folder hierarchies to locate and index SKILL.md files across up to five levels, extracting metadata like name, description, location, and depth for centralized skill cataloging and retrieval in large repositories.

Mid-level nesting enables scalable skill organization by structuring related capabilities into deeper categories, allowing teams to maintain large skill catalogs with logical hierarchy while preserving discoverability and retrieval performance.

Yes. Directory traversal across nested folders identifies SKILL.md documents and generates concise machine-readable representations suitable for vector indexing, enabling automated skill discovery, cataloging, and organization in management systems.

Mid-level nesting supports scalable categorization for large skill repositories, handling multi-level directory structures that grow beyond single-category organization while maintaining systematic skill retrieval and indexing capabilities.

Skill indexing extracts name, description, filesystem location, and nesting depth from SKILL.md files across nested directories, producing structured metadata suitable for vector indexes and enabling organized skill retrieval in management systems.

Deeper nesting becomes necessary when managing extensive skill catalogs requiring logical grouping across multiple category levels, enabling teams to structure related capabilities without losing discoverability across up to five nested levels.