Graph Schema

This is a comprehensive data modeling guide for property graph databases like Neo4j, Memgraph, and Neptune. It gives you 46 rules organized by priority, from critical entity classification and relationship design down to scale and evolution patterns. The philosophy is modeling correctness first, performance second. You get real Cypher examples comparing wrong vs right approaches, coverage of common anti-patterns like porting relational schemas directly or creating god nodes, and concrete patterns like intermediary nodes and timeline trees. The categorization by impact is smart because it tells you what actually matters when you're designing a schema from scratch or refactoring one that's producing awkward queries. Worth having loaded when you're translating a domain into graph structure.

skills.sh installs: 233
GitHub stars: 222
last updated: Aug 21, 2026

View on GitHub

Install

$ npx -y skills add pproenca/dot-skills --skill graph-schema --agent claude-code

Installs into .claude/skills of the current project.

Files

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.