Codag Visualizer
Visualize AI/LLM workflows in your codebase.
Codag analyzes your code for LLM API calls and AI frameworks, then generates interactive workflow graphs — directly inside VSCode.
You're building an AI agent that chains 3 LLM calls across 5 files. A prompt change breaks something downstream. Which call? Which branch? You grep for openai.chat, open 8 tabs, and mentally trace the flow. Again.
Or you're onboarding onto someone's LangChain project — 20 files, tool calls inside tool calls, retry logic wrapping everything. The README says "it's straightforward." It's not.
4 Reviews
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For anyone wiring up multi-step LLM systems, a map of the prompt and tool flow is exactly the artefact you wish existed. It picked up my retrieval and generation steps and showed how they connect. I would add a way to annotate a node with its eval results so the graph carries quality, not just structure.
Visualising where models, prompts and agent calls actually live in a codebase is a real need as these systems sprawl, and this renders them clearly rather than producing decorative spaghetti. On a service with a few interleaved chains it laid out the flow accurately and let me click into each node. My reservations are about scale, since a large system will produce a dense graph that needs filtering and grouping to stay readable, and about keeping the view in sync as the code changes. Even with those caveats it gave me a faster mental model of an unfamiliar AI pipeline than reading the source did.
Seeing the LLM and agent workflows tangled inside a codebase drawn out as a graph made a mess legible in minutes. It correctly traced a chain I had half forgotten. Edge labels for the call types would take it from useful to indispensable.
It draws the AI workflow hiding in your code and suddenly you can see the thing. Pointed it at a project, got a clear map, found a dead path I forgot to delete. Quietly handy.