parse-knowledge

To convert unstructured notes into structured Markdown knowledge vault files, this Skill parses raw text input to identify Areas, Topics, and Atomic Concepts, then automatically generates modular interlinked Markdown notes with consistent YAML frontmatter.

Parsing raw text into atomic Concept notes with Wikilinks involves analyzing the input to extract discrete concepts, then writing individual notes to the 40_知识 base directory while interlinking them back to the main Topic note using Wikilinks.

The required YAML frontmatter schema for OrbitOS vault notes enforces specific metadata fields including creation date, note type, area classification, and tags to ensure consistent knowledge graph integration across all generated Markdown files.

You cannot use a custom template as the Skill strictly enforces the 99_系统/模板/Wiki_Template.md for generating atomic notes, ensuring all parsed knowledge conforms deterministically to the OrbitOS vault structure and frontmatter requirements.

Yes, the knowledge parser works with existing Areas and Wiki topics by applying knowledge ingestion workflows across them, generating deterministic main notes at 30_研究/<Area>/<Topic>.md and atomic notes at 40_知识库/<Category>/<ConceptName>.md.

Limitations of automating Markdown knowledge ingestion include strict adherence to the OrbitOS vault directory structure and the Wiki_Template.md, meaning it cannot parse text into arbitrary folder hierarchies or apply different frontmatter schemas.