Neo4j
Tools Intermediate 1 year experience
Summary
I use Neo4j as a graph database for structural code intelligence. In the Copilot Agent Pipeline project, Neo4j indexes 10,000+ functions across 1,000+ files in a legacy enterprise codebase, capturing caller-callee relationships that are invisible to text-based search. Agents query the graph to map scope, trace dependencies, and identify complexity hotspots before writing or reviewing code.
How I Apply This Skill
- Indexed 10,000+ functions across 1,000+ files and 22 modules into a Neo4j graph with edges representing caller-callee relationships
- Wrote Cypher queries for structural analysis: direct callers, direct callees, full call trees at configurable depth, and cyclomatic complexity scoring
- Built a researcher agent that queries the graph to map which functions are in scope, which modules have dependencies, and where complexity concentrates before any code is written
- Enabled a skill-builder agent to query Neo4j for deep domain context exploration, tracing call trees and identifying module boundaries before packaging knowledge into structured skill files
- Used graph queries to identify the 20 most-called functions in a module and functions with cyclomatic complexity above thresholds, replacing what would have required reading hundreds of files
Key Strengths
- Graph modeling: designing node and relationship schemas that capture structural code relationships
- Cypher queries: traversal patterns for call trees, dependency chains, and complexity analysis
- AI integration: connecting graph query results to LLM agent context for structurally-informed code generation and review
- Scale: performant queries against a 10,000+ node graph with complex relationship patterns