Identifies knowledge gaps in markdown vaults, ranks them by priority, generates research questions, and offers long-tail sampling to break confirmation bias.
Scans markdown vaults to identify concepts mentioned but not defined, ranks gaps by priority, and generates research questions or random long-tail topics to fill knowledge gaps.
Enables AI agents to explore and analyze a markdown vault as a traversable knowledge graph, with tools for searching, traversing, and finding implicit semantic connections between notes.
Enables semantic recommendation for Obsidian vaults, allowing users to find related notes, forgotten knowledge, and missing connections through embedding similarity and wiki-link graph analysis.
Provides retrieval and graph tools for agents to search, backlink, and navigate a markdown-based knowledge vault, enabling hybrid search and serendipitous discovery.