graphify

Convert documents and files into a structured knowledge graph with cluster detection.

Updated Jun 23, 2026
One-click install
npx skills add https://github.com/guideops/agentic-shared --skill graphify-guideops
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: graphify
Source: https://github.com/guideops/agentic-shared/tree/main/skills/graphify
Command: npx skills add https://github.com/guideops/agentic-shared --skill graphify-guideops

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires networkx, networkx, graphviz, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill processes a wide array of input files such as code, documentation, papers, and images, and generates a structured knowledge graph, facilitating the exploration of interconnected concepts and efficient data organization.

Core Features & Use Cases

  • Input Transformation: Handles diverse file types like code, documents, papers, and images.
  • Graph Construction: Converts input data into a knowledge graph.
  • Community Detection: Identifies clusters of related concepts within the graph.
  • Output Generation: Generates interactive HTML, JSON, and audit reports.
  • Use Case: For researchers who need to map out connections between research papers and codebases, or for software developers seeking a deeper understanding of their codebase's architecture.

Quick Start

To use the graphify skill, navigate to your directory of files or specify a path using the command '/graphify /path/to/folder'.

Frequently Asked Questions about graphify

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

FAQPage Schema
How do I build a knowledge graph from multiple research papers and code files?

You can construct a knowledge graph from research papers and code by transforming diverse file inputs into a structured network. This process extracts meaningful connections and organizes interconnected concepts for efficient data exploration.

What is community detection in semantic data analysis and how does it identify clusters?

Community detection in semantic data analysis identifies clusters of related concepts within a knowledge graph by applying graph algorithms to group interconnected nodes. This reveals hidden structures and relationships across your connected data.

Can I convert a directory of unstructured documents into an interactive knowledge graph?

Yes, you can convert a directory of unstructured documents into an interactive knowledge graph by specifying a folder path. The Skill processes the files and generates interactive HTML, JSON outputs, and audit reports.

Does knowledge graph construction with networkx require separate visualization tools?

Knowledge graph construction with networkx handles node and edge creation, while visualization is supported through graphviz. The Skill integrates both dependencies to generate interactive HTML outputs for exploring interconnected concepts.

What file types are supported for semantic analysis and graph construction?

Semantic analysis and graph construction support a diverse collection of input files including code, documentation, research papers, and images, allowing you to map out connections across heterogeneous data sources.

What is the best way to visualize connections between a codebase and research papers?

The best way to visualize connections between a codebase and research papers is to generate a structured knowledge graph. This detects clusters and outputs interactive HTML and JSON files for architectural and conceptual exploration.