Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Ingests OSINT data from CSV, JSON, or API sources and builds a Neo4j knowledge graph. Runs graph algorithms including Louvain community detection, PageRank, Betweenness centrality, and Shortest Path to surface relationships between entities. All analysis runs locally against a Neo4j instance.
Graph-based analysis surfaces indirect connections and community structures that flat spreadsheets or manual link analysis cannot reveal.
When to use it
- Mapping connections between social media accounts in an investigation
- Identifying the most central nodes in a threat actor network
- Tracing indirect relationships between two named entities
- Detecting clusters of accounts coordinating together
- Auditing your own digital exposure surface
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Find communities and key influencers among a set of accounts from a CSV export
- 1Ingest nodes.csv and edges.csv into the Neo4j graph
- 2Run Louvain community detection to cluster related accounts
- 3Run PageRank centrality to rank accounts by influence score
- 4Trace shortest path between two flagged entities
- 5Export full graph to graph.json for visualization
Community clusters and ranked influencer list written to graph.json, ready for D3.js or Cytoscape rendering
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.