Knowledge Graph Builder
This tool automatically constructs knowledge graphs from text data, streamlining information organization and analysis for deeper insights.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add knowledge-graph-builder npx -- -y @trustedskills/knowledge-graph-builder
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"knowledge-graph-builder": {
"command": "npx",
"args": [
"-y",
"@trustedskills/knowledge-graph-builder"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The Knowledge Graph Builder skill enables AI agents to automatically construct knowledge graphs from text data. It transforms unstructured information into a structured format, representing entities and their relationships as nodes and edges respectively. This allows for enhanced reasoning capabilities, fact verification, and deeper insights compared to traditional methods like document-based search or relational databases. The tool focuses on making implicit relationships explicit within a domain.
When to use it
- When your domain involves complex entity relationships (e.g., people, organizations, products).
- To verify AI-generated facts against structured knowledge.
- For semantic search and traversing relationships between data points.
- When needing to answer queries like "how are X and Y related?".
Key capabilities
- Ontology Design: Defines entities (nodes), relationships (edges), and properties for a specific domain.
- Entity Types: Supports Person, Organization, Location, Product, Concept, Event, and Document entity types.
- Relationship Types: Includes Hierarchical (IS_A, PART_OF, REPORTS_TO), Associative (WORKS_FOR, LOCATED_IN, AUTHORED_BY, RELATED_TO), and Temporal relationships (CREATED_ON, OCCURRED_BEFORE, OCCURRED_AFTER).
- Property Definition: Allows for defining attributes for both nodes (e.g., id, name, type) and edges (e.g., type, confidence).
Example prompts
- "Build a knowledge graph from this document describing the company Acme Corp."
- "Create an ontology to represent relationships between people and organizations in the tech industry."
- “What are the hierarchical relationships between different types of software?”
Tips & gotchas
- Requires careful design of the domain's ontology (entities, relationships, properties) for optimal results.
- Not suitable for simple tabular data or purely document-based search scenarios; relational databases and RAG with vector DB are better alternatives in those cases.
- A team with some graph modeling expertise is beneficial to effectively utilize this skill.
Tags
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