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Graphify Knowledge Graph

Turns a folder of code, docs, or media into a persistent, queryable knowledge graph

Source Download skill
Repository
Graphify-Labs/graphify
Stars
140,829
Licence
Apache-2.0
Files
15 files

What it does

Once installed, the agent can scan a folder (code, docs, papers, images, video, or GitHub repos) and build a knowledge graph of how the pieces connect, including clusters of related concepts and the most central 'god nodes'. The graph is saved to a graphify-out/ folder and can be queried later for architecture questions, file relationships, shortest paths between concepts, or plain-language explanations of a node, instead of re-reading everything each session. It can also export interactive HTML, JSON, SVG, GraphML, Neo4j or FalkorDB files, and run as an MCP server.

Great for

  • Developers trying to understand an unfamiliar or large codebase
  • Teams wanting a persistent map of architecture and documentation
  • Researchers linking papers, notes and images into one searchable graph

Skip it if

  • Tiny projects where reading a few files is faster, since building a graph adds setup and cost
  • Sensitive or confidential repositories when pushing to Neo4j/FalkorDB or fetching URLs, because data may leave the machine or be sent to a model provider
  • Users expecting fully verified answers: edges are labelled INFERRED or AMBIGUOUS and may be wrong

Try asking

  • “/graphify . to build a knowledge graph of the current project and open the HTML view”
  • “/graphify query "How does authentication reach the database?"”
  • “/graphify path "AuthModule" "Database" to find the shortest connection between two concepts”
  • “/graphify https://github.com/owner/repo --branch main to clone and map a public repo”
Step-by-step guide: how to use Graphify Knowledge GraphInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 15 original files, the Apache-2.0 licence and an attribution note.

    graphify.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip graphify.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip graphify.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Run /graphify once, then ask normal questions about the codebase; the agent will use the saved graph first
  • Use --update for incremental rebuilds rather than re-extracting everything
  • Treat INFERRED and AMBIGUOUS edges as leads to verify in the source code

What's inside

  • __init__.py
  • __main__.py
  • _minhash.py
  • affected.py
  • always_on/agents-md.md
  • always_on/antigravity-rules.md
  • always_on/claude-md.md
  • always_on/gemini-md.md
  • always_on/kiro-steering.md
  • always_on/vscode-instructions.md
  • analyze.py
  • benchmark.py
  • cargo_introspect.py
  • cluster.py
  • skill.md

Redistributed unmodified from Graphify-Labs/graphify under the Apache-2.0 licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.