I canceled my AI code reviewer and wrote a free local one
Review the Python you changed, not the Python you inherited. Git-aware AST code review that runs in the seconds before git push. - mukundzha/avouch
In plain words
Avouch is a free, local code review tool for Python that analyzes only the code changes a developer made, not existing code. It runs as a pre-commit check before pushing to Git, using abstract syntax tree analysis to catch issues in seconds. The tool is designed for developers who want code review without relying on AI services.
written from the facts on this page · September 2026
Does the same job
all alternatives →
Kilo Code ReviewerJan 2026 · kilo.ai · ▲801Automatic AI-powered code reviews the moment you open a PR
- LALlamaPReview – AI GitHub PR reviewer that learns your codebase2024 · github.com · ▲102
I built LlamaPReview to solve a common frustration: most AI code reviewers either require complex setup or don't truly understand project context. Key differentiators: 1. One-click installation through GitHub Marketplace - no configuration needed 2. Analyzes your entire codebase first to understand: - Project structure - Coding patterns - Naming conventions - Architecture decisions 3. Completely free with no usage limits 4. Fully automated PR reviews with zero human intervention required Technical implementation: - Built on top of llama-github (my open source project) - Focuses on deep code…
- WBWe built an AI to review your pull requests2025 · infinitcode.ai · ▲53
Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
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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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Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
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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