Codebook
The Git for Prompts
What it does
Codebook scans your local repos, prompts, and git history, then groups prompts by commit so you can find a past feature, review the prompts behind it, and share them in one click. It can also sync prompts into a /prompts folder with GitHub. With codebook, you can also see a prompt dashboard across your harnesses, search and install skills from github in one click, generate diagrams of your codebase, and keep your agents.md and claude.md in sync.
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/
- GBGitBook – Build beautiful programming books using GitHub and Markdown2014 · gitbook.io · ▲442
- PLPromptr, let GPT operate on your codebase and other useful goodies2023 · github.com · ▲109
Hi HN, I've been working on an experimental tool that helps you use GPT to work on your codebase. I'd love to improve the tool if there's interest. New ideas welcome! I think this could also be useful for experimenting with other types of recursive prompts. It’s a little bit Swiss Army knife and a little bit skynet: https://github.com/ferrislucas/promptr From the README: Promptr is a CLI tool for operating on your codebase using GPT. Promptr dynamically includes one or more files into your GPT prompts, and it can optionally parse and apply the changes that GPT suggests to…
- GJGitNotebooks – Jupyter Notebook Review Tool2024 · app.gitnotebooks.com · ▲28
Hey HN, would love some feedback on our Jupyter Notebook review tool! We help data science teams check one another's work and share knowledge that's stored in Jupyter Notebooks. Currently, we integrate with GitHub, allowing for review comment submissions, pull request approval, comments on markdown and code cells that sync with GitHub. Happy to answer any questions!
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 19d ago · company-app.joinastute.com
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…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com