An AI reviewer, running on cloud, reading pull requests and catching the bugs before they ship.
A pool of autonomous OpenHands agents. Each one watches a set of GitHub repositories. When a pull request opens, GitHub fires a webhook, the agent wakes up in under a second, explores the codebase, and posts a review with real file and line citations.
Asleep by default, awake only when there is work.
Each agent is a sandbox parked to disk with zero memory cost while idle. GitHub webhooks wake them up. Reviews take a couple of minutes; the rest of the day they are checkpointed. That is how the whole pool runs for the price of a coffee.
Reviews posted so far, across the watched repositories.
Each review is a markdown comment on the pull request. Sections: summary, architecture, issues with severity and line numbers, cross-file impact, assessment. The agents are told to cite real files they read and to flag nothing if nothing is wrong.
The latest pull requests the pool has read.
Each line is a review posted on GitHub. Click through to read the full markdown comment on the pull request itself.
A note on what this is and isn’t.
Each review is written by an OpenHands agent — the same open-source software-engineering SDK that powers OpenHands Cloud — given a terminal and a file editor inside a cloned copy of the repository. The agent decides on its own what to read and how to reason about the diff.
The agents run on Orb Cloud, which checkpoints them to disk the moment they are idle and restores them in under a second when a webhook arrives. The language model is connected via LiteLLM, which lets us swap providers without code changes.
Reviews are automated opinions. They can be wrong. They are meant to be read, rebutted, or ignored.