this is a great tool, until you try reading the rule files, I had find a translator to make heads of it. given that it is CLI tool is great dev the tinker with it at no additional cost.
Open Code Review – An AI-powered code review CLI tool
51–60 of 89 posts
Re: Open Code Review – An AI-powered code review CLI tool
#52i did something like this, but somewhat in reverse. you are the one that reviews the code and you instruct AI what to do through code review comments: https://parley.cloudflavor.io . thinking about it, it would be funny to first run alibaba's tool and then run parley after. posted it here a few days ago: https://news.ycombinator.com/item?id=48369782 i guess with AI there are too many Show HN now, and i never got any…
Just a small note, the font on your site is very annoying to read, the characters are not aligned horizontally (Windows w Chrome). Looks to be a scaling issue, if I zoom to 200% it shows fine.
ah, sorry about that - will try to see what is going on. thanks for letting me know!
Re: Open Code Review – An AI-powered code review CLI tool
#53[flagged]
Re: Open Code Review – An AI-powered code review CLI tool
#54Rule files are in https://github.com/alibaba/open-code-review/tree/main/intern... (in Chinese)
An English rendering of the Java.md (Google Translate): https://github-com.translate.goog/alibaba/open-code-review/b...
And for comparison, here's a GitHub gist with three versions, first the original Chinese one, then the Google Translate version you put and finally a translated done with ChatGPT Pro: https://gist.github.com/embedding-shapes/7a51d565214bd676890...
Done that way mainly to see how the Google Translate version compared with a ChatGPT translation (revision: https://gist.github.com/embedding-shapes/7a51d565214bd676890...)
Re: Open Code Review – An AI-powered code review CLI tool
#55If you've codex what does it add over codex's default app? I am confused. Can't you simply ask codex in another tab to just do a code review?
Mechanics of running their command aside, I think the main value add is all the rules: https://github.com/alibaba/open-code-review/tree/main/intern...
Like with "SKILL" files in general, it's got to do with Prompt Engineering: https://en.wikipedia.org/wiki/Prompt_engineering#Rationale
Re: Open Code Review – An AI-powered code review CLI tool
#56Earlier quoted context omitted.
> Can't you simply ask codex in another tab to just do a code review? You are likely to get better results if you do not use the same model for review that wrote the code. I typically use Opus for code editing and GPT 5.5 for peer review using an automation with skills. Training set is different between models. If there are gaps in coverage in one model, you want a different model reviewing the work. The second model…
> You are likely to get better results if you do not use the same model for review that wrote the code There’s no evidence of this. I guess you are anthropomorphising models (i.e., it’s good that - different human reviews your code)
Yeah, one model over another seems to matter less, they respond differently to the same prompts, so if anything, I'd use multiple prompts over choosing one model over another.
However, using two models to generate two reviews easily beats doing one model and one review, as some models seem to "care" more about certain things, but you'll just miss different things if you change the model rather than add more.
Re: Open Code Review – An AI-powered code review CLI tool
#57Earlier quoted context omitted.
Finding problems is optimizing for the customer. Avoiding false positives is optimizing for the developer. Which is right depends on your org's culture.
If I flag every line in your PR as a potential security bug then I have 100% recall. Obviously you need a mixture of high recall and low false positive rate. If 7/8 flagged items are fine its much more likely people will ignore the warnings, much like they would any security tool with a 90% false positive rate. That is not optimized for the customer.
> If I flag every line in your PR as a potential security bug then I have 100% recall.
No. A code review isn't about "flagging a line of code", it's about identifying an issue or a risk. If a 10-line PR has one issue and you leave a comment on every single character, if you still miss the issue you have 0% recall.
Re: Open Code Review – An AI-powered code review CLI tool
#58I'm interested in trying this. We have our own internal automated review which has shown positive results, but I would love to drop it if I find something better. Code review is currently our bottleneck, so any possibility of better automating it is welcome.
Thermonuclear suggested by someone below is good. Matt Poccock did a demo/breakdown of that: https://www.youtube.com/watch?v=mh5XZ-L5SFQ. He has his own "improve-codebase-architecture" skill: https://github.com/mattpocock/skills/blob/main/skills/engine...
Some of them are about general coding guidelines and code quality, not necessarily vetting your current PR against specs! There's AbsolutelySkilled with clean-code and clean-architecture. Linking to older version of repo because they seem to be no longer on trunk: https://github.com/AbsolutelySkilled/AbsolutelySkilled/tree/...
I've been creating some rules to help with my Java coding: https://github.com/bitkentech/shipsmooth/tree/main/skills/ex.... These are assembled into a SKILL file when this skill file template is built: https://github.com/bitkentech/shipsmooth/blob/main/skills/ex...
Re: Open Code Review – An AI-powered code review CLI tool
#59Earlier quoted context omitted.
I would say that recall is the most important metric here though. I'd want it to catch all the issues. False positives are easy to ignore.
What, no they're not. You still need to analyze them to understand they are false positives. It's time wasted
Agree, it's something that will eventually teach your developers to ignore points raised as it's mostly garbage.
Re: Open Code Review – An AI-powered code review CLI tool
#60A repo with the English translation of each of the rules files, using Google Translate: https://github.com/pramodbiligiri/open-code-review-rules.
The original rules files (in Chinese): https://github.com/alibaba/open-code-review/tree/main/intern...