wiki-export

Installation
SKILL.md

Wiki Export — Knowledge Graph Export

You are exporting the wiki's wikilink graph to structured formats so it can be used in external tools (Gephi, Neo4j, custom scripts, browser visualization).

Before You Start

  1. Read .env to get OBSIDIAN_VAULT_PATH
  2. Confirm the vault has pages to export — if fewer than 5 pages exist, warn the user and stop

Step 1: Build the Node and Edge Lists

Glob all .md files in the vault (excluding _archives/, _raw/, .obsidian/, index.md, log.md, _insights.md).

For each page, extract from frontmatter:

  • id — relative path from vault root, without .md extension (e.g. concepts/transformers)
  • labeltitle field from frontmatter, or filename if missing
  • category — directory prefix (concepts, entities, skills, references, synthesis, projects, or journal)
  • tags — array from frontmatter tags field
  • summary — frontmatter summary field if present

This is your node list.

For each page, Grep the body for \[\[.*?\]\] to extract all wikilinks:

  • Parse each [[target]] or [[target|display]] — use the target part only
  • Resolve the target to a node id (normalize: lowercase, spaces→hyphens, strip .md)
  • Skip links that point outside the node list (broken links)
  • Each resolved link becomes an edge: {source: page_id, target: linked_id, relation: "wikilink", confidence: "EXTRACTED"}
  • If the linking sentence ends with ^[inferred] or ^[ambiguous], override confidence accordingly

This is your edge list.

Step 2: Assign Community IDs

Group pages into communities by tag clustering:

  • Pages sharing the same dominant tag belong to the same community
  • Dominant tag = the first tag in the page's frontmatter tags array
  • Pages with no tags get community id null
  • Number communities starting from 0, ordered by size descending (largest community = 0)

This enables community-based coloring in the HTML visualization and tools like Gephi.

Step 3: Write the Output Files

Create wiki-export/ at the vault root if it doesn't exist. Write all four files:


3a. graph.json

NetworkX node_link format — standard for graph tools and scripts:

{
  "directed": false,
  "multigraph": false,
  "graph": {
    "exported_at": "<ISO timestamp>",
    "vault": "<OBSIDIAN_VAULT_PATH>",
    "total_nodes": N,
    "total_edges": M
  },
  "nodes": [
    {
      "id": "concepts/transformers",
      "label": "Transformer Architecture",
      "category": "concepts",
      "tags": ["ml", "architecture"],
      "summary": "The attention-based architecture introduced in Attention Is All You Need.",
      "community": 0
    }
  ],
  "links": [
    {
      "source": "concepts/transformers",
      "target": "entities/vaswani",
      "relation": "wikilink",
      "confidence": "EXTRACTED"
    }
  ]
}

3b. graph.graphml

GraphML XML format — loadable in Gephi, yEd, and Cytoscape:

<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/graphml">
  <key id="label" for="node" attr.name="label" attr.type="string"/>
  <key id="category" for="node" attr.name="category" attr.type="string"/>
  <key id="tags" for="node" attr.name="tags" attr.type="string"/>
  <key id="community" for="node" attr.name="community" attr.type="int"/>
  <key id="relation" for="edge" attr.name="relation" attr.type="string"/>
  <key id="confidence" for="edge" attr.name="confidence" attr.type="string"/>
  <graph id="wiki" edgedefault="undirected">
    <node id="concepts/transformers">
      <data key="label">Transformer Architecture</data>
      <data key="category">concepts</data>
      <data key="tags">ml, architecture</data>
      <data key="community">0</data>
    </node>
    <edge source="concepts/transformers" target="entities/vaswani">
      <data key="relation">wikilink</data>
      <data key="confidence">EXTRACTED</data>
    </edge>
  </graph>
</graphml>

Write one <node> per page and one <edge> per wikilink.


3c. cypher.txt

Neo4j Cypher MERGE statements — paste into Neo4j Browser or run with cypher-shell:

// Wiki knowledge graph export — <TIMESTAMP>
// Load with: cypher-shell -u neo4j -p password < cypher.txt

// Nodes
MERGE (n:Page {id: "concepts/transformers"}) SET n.label = "Transformer Architecture", n.category = "concepts", n.tags = ["ml","architecture"], n.community = 0;
MERGE (n:Page {id: "entities/vaswani"}) SET n.label = "Ashish Vaswani", n.category = "entities", n.tags = ["person","ml"], n.community = 0;

// Relationships
MATCH (a:Page {id: "concepts/transformers"}), (b:Page {id: "entities/vaswani"}) MERGE (a)-[:WIKILINK {relation: "wikilink", confidence: "EXTRACTED"}]->(b);

Write one MERGE node statement per page, then one MATCH/MERGE relationship statement per edge.


3d. graph.html

A self-contained interactive visualization using the vis.js CDN (no local dependencies). The user opens this file in any browser — no server needed.

Build the HTML file by:

  1. Generating a JSON array of node objects for vis.js:
{id: "concepts/transformers", label: "Transformer Architecture", color: {background: "#4E79A7"}, size: <degree * 3 + 8>, title: "concepts | #ml #architecture", community: 0}
  • Color by community (cycle through: #4E79A7, #F28E2B, #E15759, #76B7B2, #59A14F, #EDC948, #B07AA1, #FF9DA7, #9C755F, #BAB0AC)
  • Size by degree (incoming + outgoing link count): size = degree * 3 + 8, capped at 60
  • title = tooltip text shown on hover: category, tags, summary (if available)
  1. Generating a JSON array of edge objects for vis.js:
{from: "concepts/transformers", to: "entities/vaswani", dashes: false, width: 1, color: {color: "#666", opacity: 0.6}}
  • dashes: true for INFERRED edges
  • dashes: [4,8] for AMBIGUOUS edges
  1. Writing the full HTML file:
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Wiki Knowledge Graph</title>
<script src="https://unpkg.com/vis-network/standalone/umd/vis-network.min.js"></script>
<style>
  * { box-sizing: border-box; margin: 0; padding: 0; }
  body { background: #0f0f1a; color: #e0e0e0; font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; display: flex; height: 100vh; }
  #graph { flex: 1; }
  #sidebar { width: 260px; background: #1a1a2e; border-left: 1px solid #2a2a4e; padding: 14px; overflow-y: auto; font-size: 13px; }
  #sidebar h3 { color: #aaa; font-size: 11px; text-transform: uppercase; letter-spacing: 0.05em; margin: 0 0 10px; }
  #info { margin-bottom: 16px; line-height: 1.6; color: #ccc; }
  .legend-item { display: flex; align-items: center; gap: 8px; padding: 3px 0; font-size: 12px; }
  .dot { width: 10px; height: 10px; border-radius: 50%; flex-shrink: 0; }
  #stats { margin-top: 16px; color: #555; font-size: 11px; }
</style>
</head>
<body>
<div id="graph"></div>
<div id="sidebar">
  <h3>Wiki Knowledge Graph</h3>
  <div id="info">Click a node to see details.</div>
  <h3 style="margin-top:12px">Communities</h3>
  <div id="legend"><!-- populated by JS --></div>
  <div id="stats"><!-- populated by JS --></div>
</div>
<script>
const NODES_DATA = /* NODES_JSON */;
const EDGES_DATA = /* EDGES_JSON */;
const COMMUNITY_COLORS = ["#4E79A7","#F28E2B","#E15759","#76B7B2","#59A14F","#EDC948","#B07AA1","#FF9DA7","#9C755F","#BAB0AC"];

const nodes = new vis.DataSet(NODES_DATA);
const edges = new vis.DataSet(EDGES_DATA);
const network = new vis.Network(document.getElementById('graph'), {nodes, edges}, {
  physics: { solver: 'forceAtlas2Based', forceAtlas2Based: { gravitationalConstant: -60, springLength: 120 }, stabilization: { iterations: 200 } },
  interaction: { hover: true, tooltipDelay: 100 },
  nodes: { shape: 'dot', borderWidth: 1.5 },
  edges: { smooth: { type: 'continuous' }, arrows: { to: { enabled: true, scaleFactor: 0.4 } } }
});
network.once('stabilizationIterationsDone', () => network.setOptions({ physics: { enabled: false } }));

network.on('click', ({nodes: sel}) => {
  if (!sel.length) return;
  const n = NODES_DATA.find(x => x.id === sel[0]);
  if (!n) return;
  document.getElementById('info').innerHTML = `<b>${n.label}</b><br>Category: ${n.category||'—'}<br>Tags: ${n.tags||'—'}<br>${n.summary ? '<br>'+n.summary : ''}`;
});

// Build legend
const communities = {};
NODES_DATA.forEach(n => { if (n.community != null) communities[n.community] = (communities[n.community]||0)+1; });
const leg = document.getElementById('legend');
Object.entries(communities).sort((a,b)=>b[1]-a[1]).forEach(([cid, count]) => {
  const color = COMMUNITY_COLORS[cid % COMMUNITY_COLORS.length];
  leg.innerHTML += `<div class="legend-item"><div class="dot" style="background:${color}"></div>Community ${cid} (${count})</div>`;
});
document.getElementById('stats').textContent = `${NODES_DATA.length} pages · ${EDGES_DATA.length} links`;
</script>
</body>
</html>

Replace /* NODES_JSON */ and /* EDGES_JSON */ with the actual JSON arrays you generated in step 1.


Step 4: Print Summary

Wiki export complete → wiki-export/
  graph.json    — N nodes, M edges (NetworkX node_link format)
  graph.graphml — N nodes, M edges (Gephi / yEd / Cytoscape)
  cypher.txt    — N MERGE nodes + M MERGE relationships (Neo4j)
  graph.html    — interactive browser visualization (open in any browser)

Notes

  • Re-running is safe — all output files are overwritten on each run
  • Broken wikilinks are skipped — only edges to pages that exist in the vault are exported
  • The wiki-export/ directory should be gitignored if the vault is version-controlled — these are derived artifacts
  • graph.json is the primary format — the others are derived from it. If a future tool supports graph queries natively, point it at graph.json
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