FriendlyReviewer reviews your PRs and MRs with the context of the ticket, your architecture, and your Knowledge Base. No subscription, no seat pricing, no persistent source code storage.
No subscription. No seats. No artificial limit on the developers who can trigger reviews.
per analyzed PR or MR. Correction validations are included in the price.
to create the repository's synthetic Knowledge Base. It avoids rediscovering everything on every review.
if the review fails technically. Cost should follow value, not incidents.
Yes, we explain part of the recipe. Rebuilding it properly is still another story.
FriendlyReviewer fetches the PR/MR, the Jira or Linear context, then focuses on what actually changed.
The repo is summarized into concise memory: architecture, conventions, sensitive areas. No need to reread the whole project every time.
The review is split into logical tasks. Multiple agents analyze them in parallel, then an aggregator deduplicates and prioritizes the findings.
Feedback is posted inline, with a summary. The goal: less noise, more actionable points.
After fixes, FriendlyReviewer rereads the relevant points. No need to pay for a full review again to check three changes.
Large PRs happen. We prefer to handle them explicitly rather than pretend they are always a good idea.
Both platforms are fully supported, with comments posted in the tool where your teams already work.
The ticket is not decoration: it is used as the source of intent to verify that the code solves the right problem.
The cost mostly comes from tokens and reasoning time. FriendlyReviewer reduces both with a tightly constrained approach.
Agents do not chat freely: they follow strict roles, formats, and review criteria.
The Knowledge Base avoids rediscovering the repository architecture on every PR/MR.
Less expensive models remain effective when they are well guided and fed with the right context.
FriendlyReviewer is designed to minimize what is known, stored, and billed. Easier to explain to IT leadership, healthier for everyone.
The reviewer is not just a commenting bot. It can be driven by the AI that is writing the code.
A workflow with `fr-agent` can start a review, wait for results, then launch validation from the development environment.
Install fr-agentThe IDE agent calls FriendlyReviewer tools directly: start, wait, validate, close. Less plumbing, more feedback loop.
Set up MCPIt starts the review, reads the comments, applies fixes, then asks FriendlyReviewer to validate that everything is good.
On successful internal runs, reviews with comments take 3 min 24 on average. Correction validations take 1 min 09. We advertise under 5 minutes and under 2 minutes to stay conservative.
We onboard teams gradually to keep reviews readable and useful.