classdiagram-to-neo4j

Extract entities, properties, and relationships from UML class diagrams into Neo4j.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/oopsyz/skills --skill classdiagram-to-neo4j
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: classdiagram-to-neo4j
Source: https://github.com/oopsyz/skills/tree/main/classdiagram-to-neo4j
Command: npx skills add https://github.com/oopsyz/skills --skill classdiagram-to-neo4j

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, anthropic, neo4j, pyyaml, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Telecom teams often rely on UML/class diagrams to capture entities, properties, and their interconnections. This skill extracts structured data from those diagrams and populates a Neo4j graph database, enabling reliable graph-based queries, lineage tracking, and reuse across tools.

Core Features & Use Cases

  • Vision-driven extraction of entities, properties, and relationships from UML class diagrams (including TMF-style diagrams, API schemas, and domain models).
  • Normalize extractions into a scalable, FQN-based data model and generate Cypher queries to populate Neo4j with provenance, versioning, and referential integrity.
  • Supports batch processing, data validation, constraints, and optional indexes for production-grade deployments.

Quick Start

Run the extraction workflow to analyze a class diagram image and load the results into a Neo4j graph.

Frequently Asked Questions about classdiagram-to-neo4j

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

FAQPage Schema
How do I extract entities and relationships from UML class diagrams into Neo4j?

To extract entities and relationships from UML class diagrams into Neo4j, this skill uses vision-driven models to parse diagram images and generates deterministic Cypher queries to populate the graph database with provenance and referential integrity.

Can I use vision models to extract data from TMF-style schema diagrams?

Yes, vision models can extract data from TMF-style schema diagrams. The skill supports vision-driven extraction of entities, properties, and relationships from TMF-style diagrams, UML class diagrams, and API schemas.

What is the best way to batch process UML diagram extraction for Neo4j?

The best way to batch process UML diagram extraction for Neo4j is using a workflow that normalizes extractions into a scalable, FQN-based data model and generates deterministic Cypher queries, supporting validation and constraints for production-grade deployments.

Does this UML to Neo4j extraction approach support data validation and indexing?

Yes, this UML to Neo4j extraction approach supports data validation and indexing. It enforces a stable identity model, data validation, constraints, and optional indexes to optimize query performance for production workflows.

How does the Cypher generation handle referential integrity for graph population?

Cypher generation handles referential integrity for graph population by normalizing extracted diagram data into a scalable, FQN-based identity model, ensuring deterministic queries that accurately map entities and relationships into Neo4j.