graph-database-expert

Design graph database schemas and optimize SurrealQL or Cypher queries.

45|4|Updated Nov 25, 2025

Search Tags:#query optimization #data modeling #surrealdb #graph database #surrealql #neo4j #cypher

Ready to run

npx skills add https://github.com/martinholovsky/claude-skills-generator --skill graph-database-expert

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: graph-database-expert
Source: https://github.com/martinholovsky/claude-skills-generator/tree/main/skills/graph-database-expert
Command: npx skills add https://github.com/martinholovsky/claude-skills-generator --skill graph-database-expert

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you design efficient graph database schemas, optimize complex queries, and implement advanced relationship patterns, ensuring your connected data is intuitive, performant, and scalable.

Core Features & Use Cases

Graph Schema Design: Create optimal schemas for nodes, edges, and properties.
Query Optimization: Tune SurrealQL or Cypher queries for speed and efficiency.
Relationship Patterns: Implement temporal, hierarchical, and weighted relationships.
Use Case: You need to design a social network graph where users can follow each other, and you want to efficiently query "friends of friends" or find the shortest path between two users.

Quick Start

Use the graph-database-expert skill to design a schema for a social network with user nodes and follow relationships.

Frequently Asked Questions about graph-database-expert

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I optimize SurrealQL graph traversals for finding friends of friends?▼

To optimize graph traversals in SurrealQL, you must design efficient schemas for nodes and edges, then tune queries to ensure performant connected-data retrieval. This involves proper indexing and relationship pattern implementation.

What is the best way to model temporal or weighted edges in a graph database?▼

Modeling temporal or weighted edges requires implementing advanced relationship patterns within your graph schema. You represent complex relationships by assigning specific properties to edges, ensuring queries traversing these weights perform efficiently.

Can I use Cypher queries for graph data modeling in SurrealDB?▼

SurrealDB primarily uses SurrealQL, but this expertise covers both SurrealQL and Cypher query languages. You can apply graph theory principles to design schemas and optimize queries regardless of whether you use Neo4j or SurrealDB.

How do I design a graph database schema for complex hierarchical relationships?▼

Designing a schema for hierarchical relationships involves structuring nodes, edges, and properties to represent parent-child or nested connections. You must implement specific relationship patterns to ensure intuitive and scalable connected data.

When should I use a graph database over a relational database for connected data?▼

You should use a graph database when representing complex relationships, such as social networks or shortest path calculations, where traversals are computationally expensive. It ensures performance and scalability for connected data queries.