graphify

Name: graphify
Availability: InStock
Author: roshannandhu

Convert diverse file types into a structured knowledge graph.

1|Updated May 23, 2026

Search Tags:#code analysis #knowledge graph #document analysis #graph visualization #community detection

Ready to run

npx skills add https://github.com/roshannandhu/Udaya_LMS --skill graphify-roshannandhu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: graphify
Source: https://github.com/roshannandhu/Udaya_LMS/tree/main/.agents/skills/graphify
Command: npx skills add https://github.com/roshannandhu/Udaya_LMS --skill graphify-roshannandhu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires graphifyy, graphifyy-detect, graphifyy-extract, graphifyy-cluster, graphifyy-analyze, graphifyy-report, graphifyy-export, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill converts diverse file types into a structured knowledge graph, revealing hidden connections and insights.

Core Features & Use Cases

Knowledge Graph Creation: Generate a graph from code, documents, papers, and images.
Community Detection: Identify clusters of related concepts.
Output Formats: Provides interactive HTML, JSON, and a plain-language report.
Use Case: For a software developer new to a codebase, use this Skill to understand the architecture and relationships between different components.

Quick Start

Use the graphify skill to create a knowledge graph from the 'codebase' directory.

Frequently Asked Questions about graphify

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

FAQPage Schema

How do I create a knowledge graph from a folder of code and documents?▼

Graphify converts a folder of diverse files into a knowledge graph by parsing code, documents, and images to reveal hidden connections. It provides interactive HTML, JSON, and plain-language reports as output formats for easy analysis.

What is the best way to visualize relationships in an unfamiliar codebase?▼

Generating a knowledge graph is an effective way to visualize relationships in an unfamiliar codebase, as it identifies clusters of related components and architecture. This reveals hidden connections and provides interactive HTML output for navigation.

Can I perform community detection on research papers and text documents?▼

Yes, you can perform community detection on research papers and text documents to identify clusters of related concepts. The skill analyzes diverse file types to group connected ideas and output structured JSON data.

Does graphify support exporting the knowledge graph to JSON?▼

Yes, graphify supports exporting the generated knowledge graph to JSON. It also provides interactive HTML for visual navigation and a plain-language report to explain the extracted insights and community clusters.

Do I need any specific dependencies to extract and analyze file contents?▼

Yes, you need the graphifyy, graphifyy-detect, graphifyy-extract, graphifyy-cluster, graphifyy-analyze, graphifyy-report, and graphifyy-export dependencies to parse and analyze file contents. These modules handle the complete extraction and reporting pipeline.