Build graph RAG context with Neo4j LLM Graph Builder
Convert a bounded document set into a Neo4j knowledge graph, inspect extracted nodes and relationships, and use it for graph-backed RAG.
npx skills add agentskillexchange/skills --skill build-graph-rag-context-with-neo4j-llm-graph-builder
Use Neo4j LLM Graph Builder when an agent workflow needs structured graph context from unstructured documents before retrieval, question answering, or analysis. The operator connects a Neo4j database, configures credentials and model settings, loads a bounded corpus, extracts entities and relationships, reviews the generated graph, and uses the graph or chat interface as a source for downstream RAG work. Invoke this instead of using a generic document parser when the important output is an inspectable knowledge graph with nodes, relationships, schema choices, and source metadata. The operator should validate the selected schema, spot-check extracted relationships, and keep source documents traceable before handing the graph to an agent. Start with a small corpus when cost, latency, or extraction quality is unknown. The scope boundary is graph construction and review for a controlled corpus. It is not a generic Neo4j listing, a replacement for data modeling, or an unsupervised ingestion pipeline for arbitrary private documents.