Alternatives
Products that do what CrossCheck does
Your team's code review rules, enforced on every PR
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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…
2025 · infinitcode.ai
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We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
Feb 2026 · docs.continue.dev
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I've been using Claude Code heavily, and kept hitting the same issue: the agent would push changes, respond to reviews, wait for CI... but never really know when it was done. It would poll CI in loops. Miss actionable comments buried among 15 CodeRabbit suggestions. Or declare victory while threads were still unresolved. The core problem: no deterministic way for an agent to know a PR is ready to merge. So I built gtg (Good To Go). One command, one answer: $ gtg 123 OK PR #123: READY CI: success (5/5 passed) Threads: 3/3 resolved It aggregates CI status, classifies review comments…
Jan 2026 · dsifry.github.io
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Blog post: https://spencerburleigh.com/blog/2026/02/13/crosscheck/ Repo: https://github.com/sburl/CrossCheck
Feb 2026 · github.com
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Hey HN! We're Charles and Dean, and we're building Stage: a code review tool that guides you through reading a PR step by step, instead of piecing together a giant diff. Here's a demo video: https://www.tella.tv/video/stage-demo-1pph. You can play around with some example PRs here: https://stagereview.app/explore. Teams are moving faster than ever with AI these days, but more and more engineers are merging changes that they don't really understand. The bottleneck isn't writing code anymore, it's reviewing it. We're two engineers who got frustrated with…
Apr 2026 · stagereview.app
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I built a CLI that detects patterns AI coding tools leave behind: empty catch blocks, hardcoded secrets, as any everywhere, comments that restate the code, god functions, SQL concatenation. 24 rules across JS/TS and Python. Zero config, runs offline, regex-based so it's fast. npx @yuvrajangadsingh/vibecheck . Also ships as a GitHub Action for inline PR annotations and standalone binaries (no Node required). Why: CodeRabbit found AI-generated PRs have 1.7x more issues than human PRs. Veracode says 45% of AI code samples have security vulnerabilities. "Vibe coding" is everywhere now…
Mar 2026 · github.com
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A bunch of companies that I spoke to had their own claude & codex OTel dashboards that showed spend + seats per month. However, none of the dashboards actually analyzed how the engineers worked with the tools and if there were any areas for improvement! That's why I created https://www.promptster.ai. Managers get aggregate level view of code quality and how that ties with team workflows (nothing on a per-engineer level). While engineers get personalized coaching on how they can save tokens while keeping output high. We also have a tool built for individuals to test their local…
Jul 2026
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Hey 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…
2024 · github.com
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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 : -…
2025 · codii.dev
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Hey HN - We're building wispbit (https://wispbit.com/) - a tool that lets you build your own AI code reviewer. We built this because we worked in big and complex codebases where we kept hitting booby traps - often the same ones. People forgot things, or quit altogether, amplifying the problem. We looked for other ways to fix this, but the solution is usually a combination of: - Writing a linter rule - too difficult and time consuming. - Writing docs and having frequent meetings on alignment - basically a full time job. - Using plug and play code reviewers - too generic and…
2025
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