Imagine handing a very thorough intern all your documents, screenshots, and files — every folder, every PDF, every note — and asking them to draw you a map of how everything connects. Then imagine being able to ask that map questions. That's roughly what Graphify does.
You type /graphify inside Claude Code (the AI coding assistant from Anthropic), and it reads through your project. It comes back with an interactive diagram, a report in plain English, and a file you can search. It spots the parts of your project that do too much, finds hidden connections you didn't notice, and explains why things were built the way they were.
The clever part is efficiency. Reading through a big project file by file is expensive — it uses a lot of the AI's attention. Graphify maps it first, so when you ask a question, the AI only needs to look at the relevant corner of the map instead of rereading everything. The creators claim it uses 71 times fewer resources per question.
The newest version also does some of its thinking entirely on your own computer, which means no extra costs and nothing leaving your machine.
If you work with an agency, a developer, or any team that builds things — ask them how they currently document decisions. A tool like this could answer the question you've always wanted to ask: why is it built this way?
Knowledge graph — a diagram that shows not just a list of things, but how they relate to each other. Like a mind map, but generated automatically.
Token — the unit of "attention" an AI uses to read text. Fewer tokens means faster, cheaper responses.
Open-source — software whose blueprint is public. Anyone can read it, use it, or improve it.
Local / on-device — when the AI works on your own computer instead of sending data to a server somewhere else.