Noodles – Turn any codebase into a diagram with Claude and Tree-sitter
I built a CLI tool that turns codebases and PRs into diagrams so you can quickly understand how things fit together. Originally made it because I couldn't follow my own AI-generated repos. Just shipped a big update: - Switched from D2 to Mermaid for rendering - Tree-sitter AST parsing + agentic flow instead of raw LLM calls. ~50x faster. - Works on any GitHub repo or PR, not just local - Dropped the web frontend, it's just a CLI now - Published as a pip package Still a ton to improve and I'm building fast. Feedback, issues, PRs all welcome.
Does the same job
all alternatives →- IBI built an AI that turns GitHub codebases into easy tutorials2025 · github.com · ▲923
https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
- IPI ported Tree-sitter to GoFeb 2026 · github.com · ▲222
This started as a hard requirement for my TUI-based editor application, it ended up going in a few different directions. A suite of tools that help with semantic code entities: https://github.com/odvcencio/gts-suite A next-gen version control system called Got: https://github.com/odvcencio/got I think this has some pretty big potential! I think there's many classes of application (particularly legacy architecture) that can benefit from these kinds of analysis tooling. My next post will be about composing all these together, an exciting project I call…
- IVInstantly visualize any codebase as an interactive diagram2024 · gitdiagram.com · ▲222
GitDiagram is an open-source micro dev-tool that I made this past week Given any public GitHub repository it generates diagrams in Mermaid.js with Claude 3.5 Sonnet I extract information from the file tree and README for details and interactivity (you can click components to be taken to relevant files and directories) Also, you can replace "hub" with "diagram" in any repository URL to access its diagram I created this because I wanted to contribute to open-source projects but quickly realized their codebases are too massive for me to dig through manually, so this helps me get started I do…
- NENoodles – Explore AI-generated codebases through interactive diagramsFeb 2026 · github.com · ▲10
I built Noodles to help me keep up with the codebases my AI tools generate. Open sourced last week, hit 400 stars in 8 days. The problem: AI assistants scaffold entire features quickly, but leave you maintaining code you didn't write. When bugs appear, you're reverse-engineering your own project. Noodles generates interactive D2 diagrams showing execution flow: - Scans the repository and identifies entry points (CLI commands, routes, UI components) - Maps how execution flows from entry to outcome - Renders interactive overlays with clickable nodes and tooltips - Updates incrementally when…
- MAMy Attempt to Organize the World of AI Dev Tools2025 · aicode.danvoronov.com · ▲101
I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
- SCStage CLI – An easier way of reading your AI generated changes locallyMay 2026 · github.com · ▲46
Hey HN! We're Charles and Dean. A few weeks ago we posted about Stage, a code review tool that guides you through reading a PR step by step - https://news.ycombinator.com/item?id=47796818. We got a lot of great feedback but also heard from many people that they wanted to have the chapters experience even before opening a PR… so we built the Stage CLI as the local, open-source version that anyone can try. Here’s a quick demo video: https://www.tella.tv/video/stage-cli-demo-f55q It works with any coding agent of your choice. The skill instructs the agent to…
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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