Summary

This ai code review tool estimates how long a pull request should take to review, from lines changed, files touched, change type, and review depth. The formula is grounded in the Cisco and SmartBear peer-review research showing effective review rates cluster around 200 to 400 lines of code per hour, and that defect detection drops once a session runs past roughly an hour. Enter your numbers and the tool returns an estimated review time in minutes, a focus-effectiveness label, and a flag for when to split the PR or run an AI first-pass before a human opens the diff. Nothing you type ever leaves your browser.

How Long Should Your Pull Request Actually Take to Review?

This free ai code review tool turns lines changed, files touched, and review depth into a time estimate, so you know when a diff is a five-minute skim and when it needs an AI first-pass before a human opens it.

Estimate your review
Developer reviewing a pull request diff with red and green code changes on dual monitors at night

Review time estimator

Enter the size and type of the change. The estimate updates as you type, and nothing you enter leaves your browser.

-- min estimated

    Reading the output

    How to read your estimate

    1. 1

      Enter the shape of the diff

      Lines changed, files touched, the type of change, and how deep this particular review needs to go.

    2. 2

      Read the time estimate

      Minutes are built from a base review rate, a risk multiplier for the change type, and a small penalty for context switching across files.

    3. 3

      Check the badges

      Focus effectiveness, whether to split the PR, and whether an AI first-pass on the diff is worth running before a human opens it.

    4. 4

      Decide how to schedule it

      A five-minute skim can happen between meetings. A 130-minute review needs a real block of calendar time, or a smaller PR.

    How it works

    What the estimate is built from

    Lines changed, not vibes

    The base rate comes from the range cited in the Cisco and SmartBear peer-review study: 200 to 400 lines of code per hour holds up, faster than that and defect detection drops. Your diff size runs directly through that rate.

    A risk multiplier by change type

    A bug fix and an infra change with the same line count are not the same review. Config and infrastructure edits get a 1.4x time multiplier, refactors 1.3x, features 1.15x, because the blast radius is bigger even when the diff is small.

    A signal for when to use AI first

    Past roughly 400 lines, or 90 minutes of estimated review time, human attention to detail measurably drops. The tool flags that threshold and tells you to run an AI first-pass on the diff before a person reads it end to end.

    Why bother estimating

    “How long will this take?” is worth answering before you start

    Most teams do not budget review time explicitly. A pull request shows up, someone opens it between meetings, and the review either gets rushed or sits for two days. Neither is great: a rushed review misses the things a second pair of eyes exists to catch, and a stalled one slows the whole team down. The estimate above is not meant to be exact to the minute. It is meant to answer one question before you open the diff: is this a five-minute skim, or does it need a real block of focused time? That decision changes how you schedule it, and whether it is worth running an AI first-pass on the diff first to flag the mechanical issues, so the human reviewer spends their attention on the judgment calls: is this the right approach, does it fit the architecture, will it still make sense in six months.

    • Reviews past roughly 400 lines show measurably lower defect-catch rates in published research
    • Config and infra changes carry more risk per line than feature code, even at the same size
    • An AI first-pass on the diff frees the human reviewer for judgment calls instead of syntax
    Two engineers pointing at a code diff on a laptop during a pull request review

    Common questions

    Is this actually an ai code review tool, or just a timer?
    It is a planning tool that sits in front of whatever you already use for review, human or AI. It does not read or judge your code; it estimates how much time a change deserves and tells you when running an AI first-pass on the diff is worth it before a human opens it.
    Where do the 200 to 400 lines per hour numbers come from?
    From the Cisco and SmartBear study “Best Kept Secrets of Peer Code Review,” based on roughly 2,500 reviews at Cisco Systems. It found effective review rates cluster in that range, and that reviewing faster than about 500 lines per hour lets real defects through undetected.
    Does my code ever leave my browser?
    No. The calculator only reads the numbers you type in, lines changed and files touched, and computes the estimate locally in JavaScript. There is no field to paste code into and nothing is uploaded anywhere.
    Why does a config change get penalized versus a feature with the same line count?
    Because blast radius does not scale with line count the same way. A five-line infra change can take down a deploy pipeline; a five-line feature tweak usually cannot. The 1.4x multiplier on config and infra reflects that extra scrutiny is warranted per line, not per feature.
    Should I really split every pull request over 400 lines?
    As a default, yes, if the change can be separated by concern without breaking each piece. The exception is generated or mechanical diffs, like a dependency bump or a rename across files, where line count is high but review depth needed is low. Use judgment; the tool flags the threshold, it does not override it.
    Is a “Low focus” result the same as saying my code is bad?
    No. It measures the review session, not the code. A 900-line refactor can be clean code and still deserve a low-focus warning, because no reviewer holds full attention for three hours straight. Pair it with a code quality check if you want the code itself scored.
    Does the estimate assume CI is already green before review starts?
    Yes. The formula estimates human or AI reading time on a diff that already passes lint and tests. If CI is still red, add a buffer: reviewers spend real time chasing failures that should have been caught before the PR was opened.

    Understand the diff before you open it

    codebasechat answers questions about your codebase in plain English, so by the time you open a pull request you already know what changed and why, and the review itself goes faster.

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