# Graphify > Map a folder or codebase into a queryable knowledge graph with the graphify CLI (local tree-sitter AST, zero LLM cost) and answer structure questions from it: 架构 / 依赖关系 / 什么调用了 X / A 和 B 怎么关联 / 这个项目怎么组织 / 知识图谱 / graphify. Trigger when the user points at a project directory and asks about its structure, wants a graph or architecture report of it, or types /graphify or $graphify. Query an existing graphify-out/ first; build one only when missing. - Skill: `2799662352/graphify-2` (Agent Skill) - Install (CLI): `npx skillmds@latest add 2799662352/graphify-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/2799662352/graphify-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: 2799662352 (https://skillmd.com/u/2799662352) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/2799662352/graphify-2 --- # graphify — code / folder → knowledge graph (in-app agent edition) graphify turns a directory into `graphify-out/` with three files: `graph.json` (the graph you query), `GRAPH_REPORT.md` (hubs, communities, surprising connections, suggested questions) and `graph.html` (clickable). Every edge is tagged `EXTRACTED` (explicit in source) or `INFERRED` (resolved by graphify), so you can tell what was read from what was guessed. Code is parsed locally with tree-sitter — no model call, nothing leaves the machine. This is the compact edition shipped with the CATIMATION app. If the user has installed the official skill (`graphify install --platform agents`), that copy replaces this one and its longer pipeline applies instead. ## Step 0 — pin the target directory - Use the folder the user named. Without one, use the current thread workspace root. Never run on `~`, a drive root, or a parent that contains other projects. - Quote paths with spaces. In PowerShell type `graphify`, not `/graphify` (the leading slash is a path separator there). ## Step 1 — make sure the CLI exists (ask before installing) ``` graphify --version ``` If that fails, tell the user graphify is missing and offer to install it: ``` uv tool install --python 3.13 "graphifyy[sql]" # preferred (isolated env) pipx install graphifyy # alternative python -m pip install --user graphifyy # last resort ``` The PyPI package is `graphifyy` (double y); the command is `graphify`. Pin Python 3.13 — networkx breaks on CPython 3.14.1. On Windows the binary lands in `%USERPROFILE%\.local\bin`; if a fresh shell still cannot find it, call it by full path (`"$env:USERPROFILE\.local\bin\graphify.exe"`). Do not install anything without an explicit yes from the user. ## Step 2 — fast path: the graph already exists If `/graphify-out/graph.json` exists and the request is a question (how does X work / what calls Y / trace Z), do NOT rebuild. Go straight to Step 4. ## Step 3 — build (local, free) ``` graphify update # ~1 min per 1000 files; writes graph.json + GRAPH_REPORT.md + graph.html ``` - `update` is the AST-only path: code via tree-sitter plus a heading/link scan of Markdown, no model call. It works from a cold start (no `graphify-out/` yet) and is the same command used to refresh later, so the graph never changes shape between builds. Do not use `graphify extract --code-only` for the initial build — it omits the Markdown layer that `update` will add anyway. - Tell the user roughly how long it will take before starting; run it in the foreground — it needs no interaction. - If the directory contains vendored bundles, minified JS, build output, media or generated mirrors, write a `/.graphifyignore` (gitignore syntax, merged on top of `.gitignore`) before extracting. Junk hubs with two-letter names (`tu`, `Yt`, `__`) in the report mean a minified file slipped in — add it to `.graphifyignore` and re-run with `--force`. - Concepts inside docs, PDFs and images are **not** in this default build (only Markdown structure is). They need a model pass: `graphify extract --backend openai` with `OPENAI_BASE_URL` / `OPENAI_API_KEY` (or `--backend claude|gemini|ollama`). Only do this when the user explicitly wants document content in the graph and provides or approves a backend — never reuse the app's image/video gateway token for it silently, and never paste keys into the chat. - Community names stay `Community N` without a backend. That is fine; the hub names in the report are what you navigate by. ## Step 4 — answer from the graph, then confirm in source ``` graphify query "" --budget 1500 graphify path "" "" # add --undirected if no directed path graphify explain "" ``` - Start with `query`; narrow with `path`/`explain`. Raise `--budget` only when the answer is clearly among the truncated nodes. - Every node carries `src= loc=L` and every edge an EXTRACTED / INFERRED tag. Open the two or three files the graph points at to verify before stating how something works; say which claims are INFERRED. - Summarize in prose with file:line citations. Do not paste raw graph output. - `GRAPH_REPORT.md` is for broad "what is this project" questions; open `graph.html` in the browser when the user wants to explore (above 5000 nodes it shows an aggregated community view). ## Keeping the graph current - After editing code in that directory: `graphify update ` (AST only). - After deleting or excluding files: `graphify update --force`, otherwise the shrink guard keeps the stale nodes. - `graphify-out/` is an artifact. Do not commit it unless the user asks; suggest adding it to `.gitignore` if the directory is a git repo. ## Boundaries - `graphify update` sends nothing anywhere. The documents pass (`extract --backend …`) sends file contents to whichever backend the user configured — say so before running it. - Do not loop: one build, one report, then answer. If extraction fails (missing grammar extra, sensitive-file skip, Python version), report the exact message and the one-line fix rather than retrying blindly.