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graphify

Analyze and visualize codebase dependencies and relationships using Python graph libraries.

1|Updated Nov 21, 2025
Search Tags:#codebase analysis#code architecture#graph analysis#software refactoring#dependency visualization
One-click install
npx skills add https://github.com/ezrelafidelynn/Portofolio --skill graphify-ezrelafidelynn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graphify
Source: https://github.com/ezrelafidelynn/Portofolio/tree/main/graphify/graphify
Command: npx skills add https://github.com/ezrelafidelynn/Portofolio --skill graphify-ezrelafidelynn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires networkx, networkit, numpy, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you analyze and visualize your codebase's structure and relationships, identifying key abstractions, surprising connections, and potential improvements.

Core Features & Use Cases

  • Graph Extraction: Automatically extract a graph of your codebase's dependencies, including calls, references, imports, and other relationships.
  • Graph Analysis: Analyze the graph to find most connected nodes (god nodes), surprising connections (cross-community edges), and suggest questions about the codebase's structure.
  • Use Case: Imagine you have a large codebase with many dependencies. Use this Skill to visualize the relationships between classes and modules, identify potential bottlenecks, and improve the overall design.

Quick Start

Use the graphify skill to build a graph from your codebase at 'src/'.

Frequently Asked Questions about graphify

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

FAQPage Schema
How do I visualize codebase dependencies to identify god nodes and architecture bottlenecks?▼

Codebase dependency visualization extracts calls, imports, and references from source code to construct graph structures, identifying highly connected god nodes and cross-community edges that signal architectural bottlenecks.

What is dependency graph analysis and how does it help with software refactoring?▼

Dependency graph analysis maps codebase relationships to reveal cross-community connections and key abstractions, guiding refactoring efforts by highlighting structural bottlenecks and potential design improvements.

Can I analyze a large Python codebase structure using networkx and numpy?▼

Yes, you can analyze large Python codebases by using networkx and networkit for graph construction, leveraging numpy and scipy to process dependency structures and identify key abstractions.

What's the best way to extract code architecture graphs from source files?▼

Extract code architecture graphs by automatically parsing source files for calls, references, and imports, building dependency networks that map structural relationships and isolate key abstractions for analysis.

Do I need specific Python libraries to build dependency graphs from my source code?▼

Yes, building dependency graphs requires Python with networkx, networkit, numpy, and scipy installed to perform graph construction, dependency extraction, and structural analysis on your codebase.

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