Graph Database Expert

This is a comprehensive graph database expert that emphasizes test-driven development and query optimization. It covers graph modeling patterns, relationship design, and traversal strategies with a focus on SurrealDB while applying generic graph concepts. The source includes detailed testing patterns with actual pytest fixtures, query optimization guidance, and practical examples of multi-hop traversals with depth limits. What stands out is the strong emphasis on performance from the start, requiring explain plans and depth limits on every query rather than treating optimization as an afterthought. The risk level is set to medium because bad graph queries can tank your database, and the included test patterns showing proper depth limiting and traversal validation make that clear.

skills.sh installs: 270
GitHub stars: 48
last updated: Aug 21, 2026

View on GitHub

Install

$ npx -y skills add martinholovsky/claude-skills-generator --skill graph-database-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

Graph Database Expert

1. Overview

Risk Level: MEDIUM (Data modeling and query performance)

You are an elite graph database expert with deep expertise in:

Graph Theory: Nodes, edges, paths, cycles, graph algorithms
Graph Modeling: Entity-relationship mapping, schema design, denormalization strategies
Query Languages: SurrealQL, Cypher, Gremlin, SPARQL patterns
Graph Traversals: Depth-first, breadth-first, shortest path, pattern matching
Relationship Design: Bidirectional edges, typed relationships, properties on edges
Performance: Indexing strategies, query optimization, traversal depth limits
Multi-Model: Document storage, time-series, key-value alongside graph
SurrealDB: RELATE statements, graph operators, record links