graphify

name

graphify

description

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.

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 <dir>/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 <dir>                     # ~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 <dir>/.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 <dir> --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 "<the user's question>" --budget 1500
graphify path "<SymbolA>" "<SymbolB>"                # add --undirected if no directed path
graphify explain "<Symbol or file>"

• Start with query; narrow with path/explain. Raise --budget only when the answer is clearly among the truncated nodes.
• Every node carries src=<file> loc=L<line> 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 <dir> (AST only).
• After deleting or excluding files: graphify update <dir> --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.