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How to answer architecture questions from the graph with Graphify

Ask plain-language questions and get scoped answers instead of grepping through files.

Who it is forAn engineer or AI agent that needs to understand how a class or subsystem works before editing it.

The problemGrep returns many matches without showing how the pieces relate, so answers take long to assemble.

The outcomeA short explanation of one concept, with its source location, community, and every connection tagged EXTRACTED or INFERRED.

What you need first

  • Python 3.10 or newer
  • uv (recommended) or pipx
  • A supported AI coding assistant, such as Claude Code, Cursor, Codex, or Gemini CLI
  • A local copy of the repository you want to map

Steps

  1. Complete the build step with /graphify . so graph.json exists in graphify-out/.
  2. Run graphify explain "APIRouter" (replace the name with a concept from GRAPH_REPORT.md).
  3. Run graphify query "<your question>" to get a scoped subgraph for a plain-language question. (inferred, check the README)
  4. Check each connection's tag: EXTRACTED means explicit in the source, INFERRED means derived by Graphify.

Prompt for your agent

Using the Graphify-Labs/graphify repo, run `graphify explain "<concept>"` on the target project at <project-path> and list its connections. Expected output is the node's source location, community, and connections with their EXTRACTED or INFERRED tags; verify that any claim you make from an INFERRED edge is labeled as inferred.

Caveat. The README example shows a FastAPI graph, so the exact query output on your repo will depend on how it parses.

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