Code dependency visualization with Graphify

What does a code dependency graph show?

A code dependency graph connects files and symbols through the relationships that actually tie them together: imports, calls, and documentation references. Clustering then groups the graph into subsystems, so both the connections and the boundaries become visible.

• Files and symbols as nodes, imports and calls as edges.
• Community clustering groups subsystems by topology, not by file path.
• God nodes and cross-cluster edges mark the modules worth reviewing first.

How do you generate a dependency graph from a repository?

Manual diagrams go stale, and IDE plugins usually stop at a single language or a single project view. Graphify parses the project with Tree-sitter AST extraction across 23 languages, then layers in docs and rationale from the same build.

• Upload a project ZIP; the hosted build needs no local install.
• Extraction starts from AST edges, then adds semantic links and notes.
• Open graph.html in the browser and keep the artifacts for reuse.

How do teams use dependency maps day to day?

Dependency maps serve three recurring moments: before a change, during onboarding, and after a release. Each moment needs the same underlying question answered quickly: what is connected to what, and what happens if this moves?

• Check blast radius before changing shared modules.
• Onboard engineers subsystem by subsystem using graph communities.
• Compare refreshed maps after major changes to catch drift early.

Hand-drawn diagrams, static analysis, or graph builds: what changes?

Hand-drawn architecture diagrams capture intent but age the moment code moves. Classic static-analysis views are precise within one language or one editor view, yet rarely connect code to docs and rationale. A graph build sits a level higher: edges come from the parsed source, clustering finds the boundaries, and the result is an artifact you can revisit instead of a screenshot.

• Hand-drawn maps document intent and drift out of date quietly.
• Single-language tooling sees one slice, not the whole repository.
• Graph builds keep edges, clusters, and notes in one inspectable artifact.

From ZIP to dependency graph in five steps

The path from a repository to a map is short. Pack the project, including the docs and diagrams you want represented. Upload it, and the hosted build parses source with Tree-sitter AST extraction across 23 languages, clusters the result into communities, and flags the god nodes. Then explore the interactive graph and read the written report before sharing the artifacts with the team.

• 1. Zip the project, including the docs you want mapped.
• 2. Upload it; the cloud build parses and clusters in one pass.
• 3. Open graph.html to explore edges and communities.
• 4. Read GRAPH_REPORT.md for the written version of the map.
• 5. Keep the artifacts with the project and refresh them after big changes.

What do god nodes and cross-community edges tell you about risk?

God nodes are the files with the most connections, and everything flowing through them inherits their risk: a change there has the widest blast radius. Cross-community edges mark integration seams, where two subsystems share a contract a refactor can break. Reading those two signals first turns a wall of nodes into a short list of places to review carefully.

• Treat god nodes as change-risk hotspots and review them first.
• Watch cross-community edges when boundaries shift between teams.
• Use both signals to rank a refactor plan before writing code.

How do you run a dependency review before a refactor?

Start from the graph and work in one direction: list the god nodes inside the change scope, then the cross-community edges the change will cross, then the modules sitting behind those edges. That short list becomes the review plan, and the blast radius is explicit before anyone opens an editor. After the refactor, refresh the map and compare.

• List in-scope god nodes and the edges that cross communities.
• Turn the list into the review plan for the change.
• Refresh after the refactor and compare maps to confirm the new shape.