A command-line tool that builds a searchable knowledge graph from code, documentation, PDFs, images, and videos, then answers questions by following their relationships.

It helps install the tool, build or update a graph, export graph views, and query paths, explanations, or affected parts of a project.

It lets you investigate a codebase or document collection through relevant connections instead of repeatedly reading whole files.

graphify — Skill for Claude Code by vinnie357/claude-skills

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add vinnie357/claude-skills --skill graphify

Clone the repo

git clone --depth 1 https://github.com/vinnie357/claude-skills

Made for: Claude Code.

Or install graphify, the plugin that ships this one along with the rest of its 2 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/vinnie357/claude-skills/graphify/github.svg)](https://agentmods.dev/skills/vinnie357/claude-skills/graphify)

Your own site

<a href="https://agentmods.dev/skills/vinnie357/claude-skills/graphify"><img src="https://agentmods.dev/badge/skills/vinnie357/claude-skills/graphify/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/vinnie357/claude-skills/graphify"><img src="https://agentmods.dev/badge/skills/vinnie357/claude-skills/graphify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,515 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium MCP Rug Pull · line 19
uvx/uv tool run commands without ==version create a rug-pull risk.

Fix: Pin the version: uvx package-name==1.2.3

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00076	$0.01515
Opus 5.5	$0.00030	$0.00606
Sonnet 5.5	$0.00015	$0.00303
Haiku 4.5	$0.00008	$0.00152

Measured 2mo ago against content hash 40591861e84d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

graphify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/tools/graphify/skills/graphify/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Graphify

Graphify converts a folder of code, docs, PDFs, images, and videos into a queryable knowledge graph. It extracts symbols and relationships locally with tree-sitter (no code leaves the machine for AST extraction), writes the graph to graphify-out/graph.json plus an interactive graph.html, and answers questions by traversing the graph instead of re-reading files.

PyPI package: graphifyy (double-y). CLI command: graphify. License: MIT. Requires Python >= 3.10.

For using graphify to reduce agent token usage during research and decomposition, load graphify-agents.

Installation

Using mise (recommended for this project)

Copy templates/mise.toml from this skill into the project's mise.toml, then run mise install. graphify is a PyPI package, so mise installs it through its pipx backend; the template pins uv as the backend installer and enables uvx mode so one mise install resolves uv then graphifyy:

[settings.pipx]
uvx = true

[tools]
python = "3.12"
uv = "latest"
"pipx:graphifyy" = "0.8.36"

mise trust && mise install     # installs python, uv, then graphifyy
graphify --version             # → graphify 0.8.36

Verify the backend sees the package before pinning a different version:

mise ls-remote pipx:graphifyy | tail -5

Alternative installation (upstream)

The project's own documented install (outside mise):

pip install graphifyy && graphify install

pip install graphifyy also accepts extras, e.g. pip install "graphifyy[all]". Available extras: pdf, office, google, video, mcp, neo4j, svg, leiden, ollama, openai, gemini, anthropic, bedrock, azure, sql, postgres, dm, terraform, chinese, all.

How Graphify Works

Scan + extract — walks the target path, classifies files (code, docs, papers, images), and runs tree-sitter AST extraction locally. AST extraction needs no LLM and no network.
Infer relationships — semantic edge inference uses a configured LLM backend (gemini|kimi|claude|openai|deepseek|ollama, auto-detected from available API keys). Skippable with --no-cluster / update.
Cluster + label — community detection groups related nodes; an LLM names the communities (skippable with --no-label).
Write outputs — graphify-out/graph.json (NetworkX node-link JSON), graph.html (interactive viz), and a markdown report.
Query — query/path/explain/affected traverse graph.json with no LLM call for the traversal itself.

Read the full file on GitHub · 126 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 126 lines · 76 tokens per session scan A 40591861e84d

Subscribe to this mod's changes

graphify is a skill published in the GitHub repository vinnie357/claude-skills (27 stars, last pushed 14d ago), licensed MIT. It adds 76 tokens to every session and 1,515 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Building agents Research

graphify next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
graphifyvinnie357/claude-skills	Skill	27	14d ago	MIT	A	76	Claude Code
imagegenopenai/codex	Skill	134k	today	Apache-2.0	A	113	Codex
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	2d ago	MIT	A	200	Claude Code, Codex
playwright-climicrosoft/playwright	Skill	100k	today	Apache-2.0	A	19	Claude Code
browser-automationopenclaw/openclaw	Skill	394k	today	MIT	A	36	Claude Code
systematic-debuggingobra/superpowers	Skill	315k	6d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	today	MIT	A	95	Claude Code