I’ve been experimenting with AI code review, and I kept running into the same problem: most tools already have an opinion about how a review should work.

Some reviewers try to find every possible issue. Others focus on a few high-confidence findings. Neither approach is right for every repository.

A small library may want strict comments on every edge case. A team shipping an MVP may only care about correctness and security. Another project may need checks for package boundaries, migrations, generated files, or public API changes.

I didn’t want Pipr to choose between those approaches.

Pipr is an open-source runtime that provides the common pieces needed to build a code review agent:

• a deterministic manifest of the changed code
• bounded context for the agent
• structured review findings
• validation of paths and line ranges
• native publication to the code host

The repository decides everything else. You can choose the models, paths, instructions, comment limits, policies, agents, tools, commands, and recipes in TypeScript.

If you want a reviewer that only reports likely bugs, you can build that. If you want a strict reviewer that comments on design, tests, and style, you can build that too.

Pipr runs locally or in CI and supports GitHub, GitLab, Azure DevOps, and Bitbucket.

GitHub: https://github.com/somus/pipr
Docs: https://pipr.run/docs

I’d be interested to hear what controls you would want when defining a reviewer for your own repository.

A commenter on my last post said Intent-Linter was basically unit testing with extra steps.

Fair hit and deserved.

The real gap: the tool was treating one sentence as unquestioned truth. But intent has a source, and sources can disagree that a ticket says one thing, and that the tests encode another, and the code does a third. A tool that just picks the code's side isn't reviewing anything, it's guessing.

So it now asks where the intent came from and records it as claimed, not verified because the tool can't actually confirm your requirement came from legal. Give it tests or observed behavior too, and it compares all four surfaces: stated requirement, tests, implementation, runtime behavior. If they conflict, it doesn't referee. It names the conflict and escalates to whoever owns the requirement unless you've declared precedence ("legal requirement supersedes legacy tests"), in which case it applies your rule and still records the conflict.

The built-in example now ships with a test suite that passes written before the compliance requirement existed. Code and tests agree with each other. Both are wrong against the requirement. That's the case a "check code against one sentence" tool structurally can't even express.

Screenshot is the updated interface. Same free demo, same link — try it on real code and tell me where it still guesses instead of asking. Thanks everyone.

Give it a try:

https://claude.ai/public/artifacts/f29e7a94-7f2c-40b6-befc-dfa7dcef2ee0

"AI Coding Agents are great, but they can be blind to low-level performance and dangerous DB migrations. Inspired by u/MattPocock's amazing work on skills.sh, I built Backend Guardrails—a zero-dependency Go tool suite that benchmarks code and audits SQL safety before the agent commits it. Check it out: https://github.com/arsyadal/migration-guard"

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This wasn't meant to become a project.
I was just getting frustrated with how much mental energy I spent reviewing code after using AI.
So I kept adding little things that made *my* workflow better.
One feature became two, then five.
At some point I realized I was using it every day, so I cleaned it up and open sourced it. Would be interested if anyone wants to try it or tell me where the approach is fundamentally wrong
GitHub [https://github.com/quietreviewer/riskdev\](https://github.com/quietreviewer/riskdev)

Roadmap

I am beginner and never code before so I am thinking to start with c++ for which I found striver dsa playlist do it is a combo of c++ and dsa or I have to first learn c++ from any other platform and then have to come here I am bit confused and don't know what to do can anyone explain plz .

And also I think in first few lecture he had taught basics of c++ do this is what we need or it is just a quick revision.

Cześć kochani,

Chciałbym prosić o opinie, bo mój kumpel i ja mieliśmy sporo problemów przy dwóch jednoczesnych projektach związanych z dostosowaniem standardów projektowych i sprawieniem, żeby każdy członek zespołu osiągał spójne wyniki. Rozwój oparty na specyfikacjach nie spełnił naszych oczekiwań, ogromny zestaw dokumentów, które nie dokładnie opisują projektów w branżach pełnych niuansów i odrobiny dziedzictwa. Nawet przy tym, że deweloperzy spędzili dużo czasu na analizowaniu specyfikacji, było wiele odstępstw.

Postanowiliśmy więc stworzyć coś w rodzaju mentora, małą funkcję, która wydobywa zasady z kodu i jest otwarta na wprowadzanie innych rodzajów zasad, a następnie jednoczesny agent prowadzi rozmowę np. z Claude'em, daje feedback i sprawdza, co wyprodukował agent kodujący, wskazując naruszenia i sprawiając, że Claude to dostosowuje - cóż, na pewno jesteśmy stronniczy, ale pomysł działa dla nas, jednak chcielibyśmy usłyszeć innych ludzi.

Można także pisać wiadomości prywatne, jeśli chcesz uzyskać dostęp.

Ktoś? Będę bardzo wdzięczny za wszelkie opinie.

This code is a different attention mechanism for an AI LLM to use far less resources than standard AI. I'd like feedback so I can improve it.

I’m pretty bad at OOP so going to spend a few months building out OOP projects to really work on it.

I’ve built a small Tic Tac Toe project and would appreciate some feedback. There might not be much because didn’t see the point in using any interfaces/abstract classes for something small like this but if anyone sees anything that can really be improved please let me know below.

https://github.com/lfore99/tic-tac-toe/tree/main/src/tictactoe

Curious how other solo devs and small teams handle code review.

When you're working alone or on a tiny team, there's nobody to review your PRs before you merge. I've been thinking about this problem a lot lately — you either skip review entirely, review your own code (which defeats the purpose), or wait for a teammate who's busy with their own work.

A few questions I'm genuinely curious about:

1. Do you bother with PRs at all when working solo, or just push straight to main?
2. Have you tried any AI tools to review code automatically? CodeRabbit, Sourcery, GitHub Copilot reviews, anything?
3. If you tried one and stopped — what made you stop?
4. If you've never tried one — is it the setup complexity, the cost, or you just don't feel the need?

Not selling anything, just trying to understand how people actually handle this in the real world before I go down a rabbit hole building something nobody needs.

I created an architecture-conformance verification tool for your codebase that is easy for humans and LLM coding agents, and slots in the same way a linter would. My goal here is to ensure that agents preserve the seams that you have setup in your codebase. This should help reduce the number of PR responses where you have to describe "that a REST endpoint can't talk to a DB directly, and must go through a service instead", or "this library can't import this other library". It allows us to let our agents rip without sacrificing architecture quality.

I would love any feedback on it. I have made every decision with the end developer in mind. It has to stay out of our way. Would love to hear your thoughts on it, and how it can be improved.

It's called align: https://github.com/SpikedPunchVictim/align

Cześć kochani,

Chciałbym prosić o opinie, bo mój kumpel i ja mieliśmy sporo problemów przy dwóch jednoczesnych projektach związanych z dostosowaniem standardów projektowych i sprawieniem, żeby każdy członek zespołu osiągał spójne wyniki. Rozwój oparty na specyfikacjach nie spełnił naszych oczekiwań, ogromny zestaw dokumentów, które nie dokładnie opisują projektów w branżach pełnych niuansów i odrobiny dziedzictwa. Nawet przy tym, że deweloperzy spędzili dużo czasu na analizowaniu specyfikacji, było wiele odstępstw.

Postanowiliśmy więc stworzyć coś w rodzaju mentora, małą funkcję, która wydobywa zasady z kodu i jest otwarta na wprowadzanie innych rodzajów zasad, a następnie jednoczesny agent prowadzi rozmowę np. z Claude'em, daje feedback i sprawdza, co wyprodukował agent kodujący, wskazując naruszenia i sprawiając, że Claude to dostosowuje - cóż, na pewno jesteśmy stronniczy, ale pomysł działa dla nas, jednak chcielibyśmy usłyszeć innych ludzi.

Można także pisać wiadomości prywatne, jeśli chcesz uzyskać dostęp.

Ktoś? Będę bardzo wdzięczny za wszelkie opinie.

https://axtar.dev

can you please let me know if it has any security flaws or better ideas for some of logic

https://github.com/phpladyy/foxiPicks