Neo4j GraphRAG Skill

When to Use

• Building GraphRAG retrieval pipelines with neo4j-graphrag Python package
• Choosing between VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever
• Writing retrieval_query Cypher fragments that traverse the graph after vector lookup
• Wiring retriever + LLM into a GraphRAG pipeline
• Debugging low retrieval quality (when to use graph traversal vs plain vector)
• Integrating Neo4j with LangChain (langchain-neo4j), LlamaIndex, or Haystack

When NOT to Use

• KG construction from documents → neo4j-document-import-skill
• Plain vector/semantic search without graph traversal → neo4j-vector-index-skill
• GDS algorithms (PageRank, Louvain, node embeddings) → neo4j-gds-skill
• Agent long-term memory → neo4j-agent-memory-skill
• Writing raw Cypher queries → neo4j-cypher-skill