Analyze Obsidian vault wikilink structure to detect orphans and missing notes.
npx skills add https://github.com/tuan3w/obsidian-vault-agent --skill vault-graph
Please help me install this Agent Skill. Skill: vault-graph Source: https://github.com/tuan3w/obsidian-vault-agent/tree/main/skills/vault-graph Command: npx skills add https://github.com/tuan3w/obsidian-vault-agent --skill vault-graph
It helps you diagnose fragmentation in your Obsidian vault by exposing structural issues like orphans, bridge concepts, missing links, and overall graph health.
Run vault-graph to analyze your vault’s wikilink network by executing the command that invokes analyze_vault_graph.py on your vault root directory.
High-intent search queries and answers about installing and using this skill.
To find orphan notes and missing links in an Obsidian vault, you can run a graph analysis script that computes wikilink structures to identify notes with zero connections and detect references pointing to non-existent notes.
Vault network analysis models your notes as a directed graph to compute metrics like PageRank and betweenness. This reveals influential notes and bridge concepts, exposing the overall knowledge graph health and structural fragmentation.
Yes, you can use networkx to map dead ends and bridge concepts by extracting the wikilink structure of your notes into a directed graph and calculating betweenness centrality to find highly connected bridge notes.
You get actionable linking recommendations from a vault graph by running a deterministic metric computation over the vault structure, then using an agent to interpret the JSON results into prioritized suggestions referencing specific note names.
Vault graph analysis only maps link structures for structural discovery. It computes metrics over the wikilink network to identify orphans and missing notes, rather than searching or parsing the actual text content within the notes.
Nero-kkExport Obsidian wiki knowledge graphs to graph.json, graph.graphml, cypher.txt, and graph.html.
Mic92Search the web via Kagi and generate AI summaries with JSON output.
SPIRAL-EDWINCompute degree, betweenness, closeness, eigenvector centrality, and PageRank for network nodes.
Hawksight-AIAnalyze graph topology and generate visual summaries of knowledge graphs.
