graphify-windows

Transform raw file folders into knowledge graphs with HTML and JSON outputs.

Updated Apr 19, 2026
One-click install
npx skills add https://github.com/saiteja007-mv/techrex-claude-setup --skill graphify-windows-saiteja007-mv
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: graphify-windows
Source: https://github.com/saiteja007-mv/techrex-claude-setup/tree/main/.claude/skills/graphify
Command: npx skills add https://github.com/saiteja007-mv/techrex-claude-setup --skill graphify-windows-saiteja007-mv

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Turns raw folders of files into a persistent knowledge graph that preserves provenance, enables cross-document connections, and outputs human- and machine-readable representations (HTML + JSON) plus an audit report.

Core Features & Use Cases

  • Persistent graph with graphify-out/graph.json, supporting community detection and cross-file relationships.
  • Honest audit trail by tagging edges as EXTRACTED, INFERRED, or AMBIGUOUS for traceability.
  • Use cases include codebases, notes, papers, and raw folders; outputs support exploration, analysis, and documentation.

Quick Start

Drop a folder into graphify and run /graphify to generate a navigable knowledge graph with outputs in HTML and JSON.

Frequently Asked Questions about graphify-windows

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

FAQPage Schema
How do I turn a raw folder of files into a knowledge graph?

To turn a folder into a knowledge graph, run the graphify command on your directory to extract and cluster file relationships, outputting navigable HTML and JSON formats.

What is a persistent knowledge graph with provenance for codebase analysis?

A persistent knowledge graph with provenance is a structured representation of files that preserves cross-document relationships and source traceability, outputting graph.json and an audit report.

Can I generate a code graph from notes and papers without losing source traceability?

Yes, you can generate a code graph from notes, papers, and media that maintains source traceability by tagging edges as EXTRACTED, INFERRED, or AMBIGUOUS for cross-document exploration.

Does the knowledge graph output support both human and machine readable formats?

Yes, the knowledge graph output supports both human and machine readable formats by generating navigable HTML for visual exploration and JSON for programmatic data access.

What is the best way to audit cross-document relationships in a raw folder?

The best way to audit cross-document relationships is to process the folder into a structured graph that tags connections as EXTRACTED, INFERRED, or AMBIGUOUS, producing a readable audit report.

Do I need the graphify framework to extract and cluster file relationships?

Yes, you need the graphify framework to extract, cluster, and output the structured knowledge graph, as it handles the core processing logic for cross-document exploration and audit trails.