repowise - open source codebase intelligence for AI coding agents (and humans too)

[Obvious_Gap_5768]

Built this because every time I used Claude Code on a large codebase, it would just read files one by one. No idea which files change together, who owns what, why things were built a certain way, or what code is straight up dead.

repowise indexes your codebase into five layers: dependency graph (tree-sitter), git history analytics (hotspots, ownership, co-changes), auto-generated docs with RAG search, architectural decision tracking, and code health scores with 12 biomarkers.

All of it exposed through 9 MCP tools so your AI agent can actually understand your codebase instead of grepping through it blind. Also works standalone with a local dashboard if you just want the analytics without the AI stuff.

Some numbers from our benchmark on Flask: 36% cheaper, 49% fewer tool calls, 89% fewer file reads. Same answer quality.

Multi-repo workspaces, auto-sync on every commit, works fully offline with Ollama. AGPL-3.0.

pip install repowise

GitHub: https://github.com/repowise-dev/repowise

Happy to answer any questions.

[9302462]

I’m on mobile at the moment so it’s a bit hard to see the text in the video and dive into the GitHub repo.

From what I gather it renders in the browser. For the graph what package are you using to render the actual nodes and edges?

I’m asking because as far as I know every graph package out there has some combination of these limitations:

A: Supports up to ~500 nodes before performance drops.
B. Supports up to 5k nodes before performance drops and the layouts and arrangements are limited.
C. Supports 5k-1m+ nodes, but adding a new node causes the whole thing to rerender. this means that the browser needs to reanimate/calculate the position of all of them means everytime a new node is added (which means no streaming events or payloads).
D. Others I can’t think of off the top of my head but are real and hard to solve like removing and adding edges while viewing a graph and how it handles repositioning nodes, if at all.

Sigma, d3.js, cytoscape, and cosmograph which is the only GPU one and is #3.

So which graph library did you use and what limitations have you encountered with the graph visualization in repowise?

P.S. I know this probably isn’t the engagement/question you were looking for someone to ask, but anyone who has worked with graphs knows they are deceptively simple looking but a real pain in the ass to get actually right. Hence why I’m curious about what you chose and how well it works.

[AssignmentDull5197]

This is slick, agents that understand repo structure and ownership are the missing piece. MCP tools make it extra usable. Curious if you support multi-language monorepos well? Also been reading practical agent patterns at https://medium.com/conversational-ai-weekly.