i built an AI code reviewer for github (used it on itself during dev)
I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
i built an AI code reviewer for github (used it on itself during dev) launched on April 19, 2025 with 6 votes and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
Ship cleaner code, faster — with Codii, your AI code review assistant.
In the maker’s words, at launch
I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the…
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I built an AI that turns GitHub codebases into easy tutorials2025 · github.com · ▲923https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
git-lrcFeb 2026 · hexmos.com · ▲300Hi HN, I'm the author of git-lrc, would appreciate some feedback from the community Last year my team started using AI coding tools more heavily, and we found ourselves generating tons of code, but spending less time looking at the stuff that's been generated. We felt like we were losing a bit of grip/understanding of what we were building. Regressions occasionally slipped through. Sometimes changes made it all the way to production only to be reverted later. We tried several AI code review tools, but most operate at PR time. That felt too late. I wanted review to happen while the…
TrailsJan 2026 · trails-red.vercel.app · ▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
We built an AI to review your pull requests2025 · infinitcode.ai · ▲53Hey 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…
LlamaPReview – AI GitHub PR reviewer that learns your codebase2024 · github.com · ▲102I 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…
Open-Source Pull Request AI Reviewer2024 · github.com · ▲5Hey HN, Over the last year, I’ve reviewed more than 1000 code changes. Most of the time was spent catching obvious mistakes rather than debating complex design decisions. If we estimate ~10 minutes per review, that’s 160+ hours spent reviewing code in just one year. So I thought: could I get some of that time back using LLMs? That's why I spent the last few weekends building Presubmit.ai, an open-source AI reviewer that runs as a Github Action right when you open a Pull Request. The results so far are promising: I estimate it can reduce the review time by 50%, which in my case would mean I…
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