| name | graph-schema |
| description | Graph database schema design and data modeling expert. Use when designing, reviewing, or refactoring graph database schemas (Neo4j, Memgraph, Neptune, etc.). Triggers on graph modeling, node/relationship design, Cypher schema, property graph design, knowledge graph modeling, or when translating a domain into a graph structure. Focuses primarily on data modeling correctness — understanding the user's goal and translating it into the right graph structure — with performance as a secondary concern. |
dot-skills Graph Database Schema Design Best Practices
Comprehensive graph database data modeling guide for property graphs (Neo4j, Memgraph, Amazon Neptune, etc.). Contains 46 rules across 8 categories, prioritized by modeling impact from critical (entity classification, relationship design) to incremental (scale and evolution). Each rule includes detailed explanations, real-world Cypher examples comparing incorrect vs. correct models, and specific impact descriptions.
Philosophy: Data modeling correctness first, performance second. Always ask "what is the user trying to achieve?" before choosing structure.
When to Apply
Reference these guidelines when:
- Designing a new graph database schema from domain requirements
- Translating a relational schema to a graph model
- Deciding whether something should be a node, relationship, or property
- Reviewing an existing graph schema for modeling errors
- Refactoring a graph that produces awkward or slow queries
- Planning for schema evolution and data growth
Rule Categories by Priority
| Priority | Category | Impact | Prefix |
|---|
| 1 | Entity Classification | CRITICAL | entity- |
| 2 | Relationship Design |
