graphify

Name: graphify
Availability: InStock
Author: kos3nz

Converts a folder of files into a knowledge graph with HTML, JSON, and report outputs.

Updated Nov 16, 2022

Search Tags:#documentation #code-analysis #graph #knowledge-graph #audit-trail #data-discovery #graph-output

Ready to run

npx skills add https://github.com/kos3nz/dotfiles --skill graphify-kos3nz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: graphify
Source: https://github.com/kos3nz/dotfiles/tree/main/.config/agents/skills/graphify
Command: npx skills add https://github.com/kos3nz/dotfiles --skill graphify-kos3nz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Turn any folder of files (code, docs, papers, images) into a navigable knowledge graph with an honest audit trail and ready-made outputs (interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPH_REPORT.md).

Core Features & Use Cases

Persistent graph: relationships survive across sessions via graphify-out/graph.json.
Honest audit trail: every edge is labeled EXTRACTED, INFERRED, or AMBIGUOUS to show evidence.
Cross-document connections: community detection reveals connections across files in different formats.
Use cases: understand unfamiliar codebases, organize reading lists, or structure a personal raw-folder corpus.

Quick Start

Drop any folder into graphify and run the CLI on that path to generate a graph, an HTML/JSON output, and an audit report.

Frequently Asked Questions about graphify

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

FAQPage Schema

How do I turn a folder of code and documents into a knowledge graph?▼

To turn a folder into a knowledge graph, run the CLI on your target path to detect files, extract cross-document relationships, and generate interactive HTML, GraphRAG-ready JSON, and a plain-language report.

What is an audit trail in a knowledge graph and why does it matter?▼

An audit trail in a knowledge graph labels every edge as EXTRACTED, INFERRED, or AMBIGUOUS to show evidence. This transparency matters because it reveals the confidence level behind cross-document connections and inferred concepts.

Can I generate a knowledge graph from mixed file formats like code, papers, and images?▼

Yes, you can generate a knowledge graph from mixed file formats. The tool detects files across code, docs, papers, and images, running deterministic and semantic extraction to reveal cross-format community connections.

How do I keep knowledge graph relationships persistent across different sessions?▼

To keep knowledge graph relationships persistent across sessions, the tool saves discovered connections to a graph.json file in the output directory, ensuring your extracted and inferred data survives for later exploration.

What is the best way to understand an unfamiliar codebase using a knowledge graph?▼

The best way to understand an unfamiliar codebase using a knowledge graph is to run extraction on the folder to discover cross-document relationships, cluster concepts, and review the generated plain-language report for navigable insights.

Does graphify require external dependencies to process files for data discovery?▼

No, graphify does not require external dependencies to process files for data discovery. It operates independently to load paths, detect files, and run deterministic and semantic extraction for your folder corpus.