understand

Analyze a codebase and generate a structured knowledge graph for the Understand Anything platform.

Updated Apr 9, 2026
One-click install
npx skills add https://github.com/cookeyholder/django-devcontainer-template --skill understand-cookeyholder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: understand
Source: https://github.com/cookeyholder/django-devcontainer-template/tree/main/.agent/skills/understand
Command: npx skills add https://github.com/cookeyholder/django-devcontainer-template --skill understand-cookeyholder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill analyzes a codebase to produce an interactive knowledge graph that reveals architecture, components, and their relationships for easier understanding and onboarding.

Core Features & Use Cases

  • Automated graph generation: Builds a structured graph of files, directories, and imports to visualize dependencies and architecture.
  • Interactive dashboard readiness: Outputs a knowledge-graph.json ready for use in a dashboard and exploration UI.
  • Use Case: On a large Django project, quickly map the Django apps, models, views, and templates into layers and edges for architecture reviews.

Quick Start

Provide a repository to the Understand Anything pipeline and run the Understand workflow to generate the knowledge graph for the current project.

Frequently Asked Questions about understand

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

FAQPage Schema
How do I generate a knowledge graph from a codebase for architecture visualization?▼

To generate a knowledge graph from a codebase, this Skill analyzes files, directories, and imports to map dependencies and architecture. It outputs a structured JSON payload ready for interactive dashboard ingestion.

What is static analysis used for when mapping code architecture and dependencies?▼

Static analysis for code architecture maps structural relationships between files and directories without executing the code. This process captures dependencies, layers, and components to form a comprehensive dependency graph.

Can I use this knowledge graph generation for a large Django project?▼

Yes, you can use this for a large Django project. It maps Django apps, models, views, and templates into distinct layers and edges, facilitating quick architecture reviews and onboarding.

How do I prepare my repository for automated dependency graph extraction?▼

Provide your repository directly to the pipeline and run the workflow. The automated analysis scans the codebase to extract non-code context and structural dependencies into a structured graph payload.

Does the generated dependency graph output support interactive dashboard exploration?▼

Yes, the dependency graph output supports interactive dashboard exploration. It produces a knowledge-graph.json file specifically structured for immediate ingestion by exploration UI and dashboard platforms.

What is the best way to visualize code components and relationships for onboarding?▼

The best way to visualize code components for onboarding is generating a structured knowledge graph. It reveals architecture, dependencies, and relationships, turning complex codebases into learnable graphs.