
PRsage
Automated AI code reviews that track commit iterations.
What it does
PRsage is an AI-powered GitHub App that automates first-pass code reviews. Instead of just leaving a single generic comment, it identifies real issues across bugs, security, and performance, while uniquely tracking iteration changes across commits. You instantly see what was fixed and what remains. Catch meaningful issues early, reduce manual effort, and ship faster with clear, structured feedback directly on your pull requests. Completely free to use.
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Kilo Code ReviewerJan 2026 · kilo.ai · ▲801Automatic AI-powered code reviews the moment you open a PR



- TTTool to Automatically Create Organized Commits for PRs2025 · github.com · ▲76
I've found it helps PR reviewers when they can look through a set of commits with clear messages and logically organized changes. Typically reviewers prefer a larger quantity of smaller changes versus a smaller quantity of larger changes. Sometimes it gets really messy to break up a change into sufficiently small PRs, so thoughtful commits are a great way of further subdividing changes in PRs. It can be pretty time consuming to do this though, so this tool automates the process with the help of AI. The tool sends the diff of your git branch against a base branch to an LLM provider. The LLM…
- EAEllipsis – Automated PR reviews and bug fixes2024 · ellipsis.dev · ▲121
Hi HN, hunterbrooks and nbrad here from Ellipsis (https://www.ellipsis.dev). Ellipsis automatically reviews your PRs when opened and on each new commit. If you tag @ellipsis-dev in a comment, it can make changes to the PR (via direct commit or side PR) and answer questions, just like a human. Demo video: https://www.youtube.com/watch?v=X61NGZpaNQA So far, we have dozens of open source projects and companies using Ellipsis. We seem to have landed in a kind of sweet spot where there’s a good match between the current capabilities of AI tools and the actual needs of…
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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.
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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…
AI · 27d ago · cactuscompute.com


Launched alongside, May 2026
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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