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shekerkamma
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graphify

Convert code, docs, papers, images, and video files into queryable knowledge graphs.

Updated May 22, 2026
Search Tags:#code analysis#knowledge graph#content extraction#natural language query#codebase exploration#graphrag#document querying
One-click install
npx skills add https://github.com/shekerkamma/peopletech-marketplace --skill graphify-shekerkamma
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graphify
Source: https://github.com/shekerkamma/peopletech-marketplace/tree/main/plugins/content-tools/skills/graphify
Command: npx skills add https://github.com/shekerkamma/peopletech-marketplace --skill graphify-shekerkamma

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the manual effort of organizing and connecting scattered project content—including code, documentation, papers, images, and video—by automatically building a searchable, navigable knowledge graph that surfaces hidden cross-content relationships.

Core Features & Use Cases

  • Multi-format knowledge graph generation: Build graphs from any mix of code, docs, papers, images, and video files, with community detection to group related concepts.
  • Flexible querying and export: Ask natural language questions about the graph, trace paths between concepts, and export to interactive HTML, GraphRAG-ready JSON, or Neo4j-compatible formats.
  • Use Case: An engineering team can run graphify on a codebase to instantly trace how an authentication module connects to database calls and related documentation, cutting hours of manual mapping work.

Quick Start

Use the graphify skill to build a knowledge graph of your current project folder and ask how the user authentication flow connects to database operations.

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 a codebase and documentation?▼

You can build a queryable knowledge graph from mixed content by automatically extracting and structuring relationships from code, docs, papers, images, and video files. This eliminates manual mapping effort by surfacing hidden cross-content connections.

Can I query a codebase knowledge graph using natural language?▼

Yes, you can query a codebase knowledge graph using natural language questions. The graph supports BFS/DFS traversal and plain-language node explanations to trace paths between concepts like authentication modules and database calls.

What is the best way to trace connections between code and related documentation?▼

The best way to trace connections between code and documentation is generating a knowledge graph with audited EXTRACTED, INFERRED, and AMBIGUOUS relationship labels. This allows you to instantly navigate how different components interact across your project.

Does GraphRAG support exporting knowledge graphs to Neo4j-compatible formats?▼

GraphRAG knowledge graphs can be exported to Neo4j-compatible formats, interactive HTML, or GraphRAG-ready JSON. This allows you to analyze codebase relationships and document connections in external graph databases or visualization tools.

How do I merge multiple repositories into a single queryable graph?▼

You can merge multiple repositories into a single queryable graph by applying incremental updates to the existing structure. This multi-repo merging capability allows you to trace connections across different project sources during cross-repo analysis.

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