Knowledge

Knowledge ingestion uses ripple effects to update related notes automatically, maintaining consistency and traceability across the archive. When ingesting sources, the system applies frontmatter schemas and propagates changes through wikilinks to keep interconnected notes synchronized.

Ripple ingestion maintains consistency by propagating changes across related notes when new sources are added. It applies frontmatter schemas and typed relationships during writes, ensuring traceability and automatic updates throughout the interconnected knowledge graph.

Yes, the archive supports a 3-pass search covering lexical content, frontmatter fields, and wikilinks. This deterministic approach locates notes across People, Companies, Ideas, and Research domains without requiring external dependencies.

The best way to manage notes across entity domains is to apply structured linking and MOC regeneration during writes. This maintains a typed, interlinked archive across People, Companies, Ideas, and Research domains with provenance tracking and graph analytics.

No dependencies are required. The archive performs graph analytics, 3-pass search, and ripple ingestion natively by applying frontmatter schemas and typed relationships such as caused-by and preceded-by directly during write operations.

Use MOC regeneration and typed relationships during write operations to ensure frontmatter schemas are applied and the knowledge graph remains consistent. This maintains traceability and enables reliable harvest and search across the archive.