A powerful tool for building Neo4j knowledge graphs from OSINT data to discover hidden connections and community patterns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install osint-graph-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install osint-graph-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is OSINT Graph Analyzer?
OSINT Graph Analyzer is a specialized utility designed to transform fragmented data from Openclaw Skills into structured, actionable intelligence. By leveraging Neo4j's graph database engine, it enables investigators and analysts to ingest data from diverse sources—including social media APIs, CSV files, and JSON Cypher queries—to build comprehensive knowledge graphs. The tool excels at identifying entity links across platforms and revealing the underlying structure of complex networks through advanced mathematical algorithms, providing a clear visual representation of otherwise hidden relationships.
OSINT Graph Analyzer Use Cases
- Map relationships and connections in complex investigative workflows.
- Identify central nodes and high-value targets within threat intelligence attack networks.
- Conduct social network analysis to uncover influence patterns and community clusters.
- Perform counter-OSINT to visualize and minimize your own digital exposure surface.
How OSINT Graph Analyzer Works
- Ingest raw data from CSV, JSON, or direct API sources into the local environment.
- Map entities and relationships to a Neo4j 5.x graph database instance.
- Apply graph algorithms like Louvain for community detection or PageRank for influence analysis.
- Execute path analysis to trace indirect chains of connection between specific entities.
- Export the analyzed graph as a visualization-ready JSON file for tools like D3.js or Cytoscape.
OSINT Graph Analyzer Setup
Ensure you have Python 3.9+ and Neo4j 5.x installed. You can launch a local instance via Docker to begin processing data for Openclaw Skills:
docker run -d --name neo4j -p 7474:7474 -p 7687:7687 -e NEO4J_AUTH=neo4j/password neo4j:5.23
Install the neo4j-driver package and ingest your data source:
python3 scripts/osint-graph.py --ingest data/sources.csv
OSINT Graph Analyzer Data Schema & Taxonomy
The skill organizes data using a node-and-edge model optimized for graph traversal and pattern recognition.
| Component | Description | Examples |
|---|---|---|
| Nodes | Individual entities identified in the data | Person, Handle, Organization, Location |
| Edges | Logical relationships between nodes | MENTIONED, FOLLOWS, LIVES_IN, WORKS_AT |
| Properties | Metadata attributes for nodes and edges | Country, Timestamp, Verification status |
OSINT Graph Analyzer Advanced Features
- Automated community detection using the Louvain algorithm for group identification.
- Bridge node discovery via Betweenness centrality to find key connection points between networks.
- Support for direct API ingestion from platforms like Telegram and Twitter using Openclaw Skills architecture.
- Local-only processing mode ensuring sensitive intelligence data never leaves your infrastructure.
- Shortest path analysis to trace the most direct connection between two disparate entities.
SKILL.md
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