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knowledge-graph-builder

Design ontologies and select graph databases for knowledge graph implementation.

14|5|Updated Jan 29, 2026
Search Tags:#knowledge graph#ontology#hybrid search#graph database#AI grounding#entity extraction
One-click install
npx skills add https://github.com/oakoss/agent-skills --skill knowledge-graph-builder-oakoss
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: knowledge-graph-builder
Source: https://github.com/oakoss/agent-skills/tree/main/skills/knowledge-graph-builder
Command: npx skills add https://github.com/oakoss/agent-skills --skill knowledge-graph-builder-oakoss

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you implement sophisticated knowledge graphs to make implicit relationships explicit, enabling AI systems to reason, verify facts, and reduce hallucinations.

Core Features & Use Cases

  • Ontology Design: Define entity types, relationships, and properties.
  • Graph Database Selection: Choose between Neo4j, Neptune, ArangoDB, and TigerGraph.
  • Hybrid Architecture: Integrate graph traversal with vector search for enhanced retrieval.
  • Use Case: You are building a recommendation engine that needs to understand complex user-product relationships. This Skill guides you through designing the graph schema, selecting the right database, and implementing a hybrid search to find related items.

Quick Start

Use the knowledge-graph-builder skill to design an ontology for a new domain.

Frequently Asked Questions about knowledge-graph-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a knowledge graph for AI grounding and hallucination detection?▼

Knowledge graph implementation for hallucination detection involves defining an ontology, extracting entities, and integrating hybrid graph-vector search. This makes implicit relationships explicit for AI fact verification.

How do I choose a graph database for my ontology design?▼

Selecting a graph database involves comparing Neo4j, Neptune, ArangoDB, and TigerGraph against your ontology design. Consider hybrid search integration, query patterns, and scalability to find related items.

What is hybrid graph-vector architecture for retrieval?▼

Hybrid graph-vector architecture integrates graph traversal with vector search for enhanced retrieval. It combines explicit relationship mapping with semantic similarity to ground AI systems.

Can I use knowledge graphs for entity resolution in a recommendation engine?▼

Knowledge graphs support entity resolution in recommendation engines by mapping complex user-product relationships. Designing a graph schema and implementing hybrid search enables precise recommendations.

What's the best way to design a graph schema for complex relationships?▼

Designing a graph schema requires defining an ontology that specifies entity types, properties, and relationships. This formal structure allows AI systems to reason and verify facts over complex data.

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