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Found 17 Skills
Expert in Spring Data Neo4j integration patterns for graph database development. Use when working with Neo4j graph databases, node entities, relationships, Cypher queries, reactive Neo4j operations, or Spring Data Neo4j repositories. Essential for graph data modeling, relationship mapping, custom queries, and Neo4j testing strategies.
Comprehensive guide for writing modern Neo4j Cypher read queries. Essential for text2cypher MCP tools and LLMs generating Cypher queries. Covers removed/deprecated syntax, modern replacements, CALL subqueries for reads, COLLECT patterns, sorting best practices, and Quantified Path Patterns (QPP) for efficient graph traversal.
Use when upgrading Neo4j drivers to new major versions
Use when working with Neo4j command-line tools including neo4j-admin, cypher-shell, aura-cli, and neo4j-mcp
Use when upgrading Neo4j 4.x and 5.x Cypher queries to 2025.x/2026.x versions
Neo4j graph database with Cypher query language. Use for graph-based data.
Use Neo4j memory MCP for creating/updating linked memories (entities, relations), de-duplication (DRY), and retrieval queries for project continuity. Use when saving global learnings or querying graph relationships.
Orchestrates the full journey from zero to a running Neo4j application. Executes 8 named stages in order: prerequisites → context → provision → model → load → explore → query → build. Each stage has its own reference file in references/ that the agent reads and follows when entering that stage. Supports both HITL and fully autonomous operation. Time budget: ≤15 min after DB is running (autonomous), ≤90 min total (HITL).
Knowledge graph specialist for entity and causal relationship modelingUse when "knowledge graph, graph database, falkordb, neo4j, cypher query, entity resolution, causal relationships, graph traversal, graph-database, knowledge-graph, falkordb, neo4j, cypher, entity-resolution, causal-graph, ml-memory" mentioned.
Graph database implementation for relationship-heavy data models. Use when building social networks, recommendation engines, knowledge graphs, or fraud detection. Covers Neo4j (primary), ArangoDB, Amazon Neptune, Cypher query patterns, and graph data modeling.
Neo4j Cypher Shell skill. Connect to instances, run Cypher queries, and retrieve full graph schemas via cypher-shell CLI.
Fully local multi-agent swarm intelligence simulation engine using Neo4j + Ollama for public opinion, market sentiment, and social dynamics prediction.