I ran 3 Claude Code architecture diagram tools on my repo. Here's what each one got right

7.6 relevance

Comparative evaluation of Claude Code architecture diagram tools on a real repo is highly actionable for developers using AI coding assistants.

AI/ML dev.to

Answer the board on AI readiness

Arrive with evidence, not opinion. See how your foundation benchmarks against your peers, get a clear read, and leave with a ranked place to start.

Why It Matters

For a platform engineer managing polyglot, multi-repo systems, this comparison reveals the hidden risks of agent-generated architecture documentation—memory-based flows and cards can be wrong—and shows which tools actually verify against live code.

Key Takeaways

Always request code-traced flows or line-verified diagrams instead of relying on agent memory when using LLM-based architecture tools.

I ran 3 Claude Code architecture diagram tools on my repo. Here's what each one got right

Summary

Three open-source Claude Code plugins—Floorplan, Archify, and Understand Anything—were tested on a multi-repo app (Python/AWS Lambda, JS site, MCP connector). Floorplan produced a clickable map with 66 endpoints but generated two incorrect user flows from agent memory, fixed by requesting code-traced flows. Archify created a single diagram with verified line links but failed twice on SSH remote and uncommitted edits, and its card descriptions were also wrong from memory. Understand Anything built a 732-node knowledge graph with a guided tour for $13 in API costs, with no errors found.

Author

Valentina Koniukhova