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GitRank

AI-powered PR scoring platform for engineering teams. Open source and self-hostable.

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AI PR scoring

AI PR scoring that explains the impact behind every merge

GitRank turns a merged pull request into an explained impact score. Instead of rewarding commit volume, it evaluates the change against the rules your organization has chosen: severity, component importance, and eligibility.

Start freeSee how it works

A score is useful only when engineers can understand and challenge it. Every evaluation includes the classification, eligibility checks, and score breakdown that produced the result.

The problem

Move from activity counts to contribution context

A one-line authentication fix can matter more than a large refactor, while a busy commit history can hide work that did not reach users. AI PR scoring gives managers and contributors a consistent starting point for discussing the work that shipped.

Built for meaningful engineering signals

A clear path from GitHub activity to better decisions

Evaluate merged work automatically

Claude analyzes the pull request diff, linked issue context, and repository configuration after merge—without adding a manual scoring step.

Use a transparent scoring model

Severity base points, component multipliers, and eligibility rules make the score legible instead of leaving contributors with a black-box grade.

Put scores to constructive use

Use the explained result for recognition, bounty programs, engineering recaps, and trend analysis—not as a substitute for thoughtful management.

How it works

From merged PR to explained score

  1. 1

    Connect the work your team already does

    Install the GitHub App, select repositories, and let GitRank receive merged pull request events automatically.

  2. 2

    Evaluate the contribution in context

    GitRank reads the merged diff, linked issues, component rules, and eligibility requirements before producing an explanation.

  3. 3

    Turn the result into a useful conversation

    Scores, summaries, and trends feed leaderboards, review workflows, bonus programs, and team discussions without relying on raw activity counts.

Practical guidance

A responsible AI PR scoring policy

  • Publish the scoring rubric before you use results in recognition or rewards.

  • Give administrators a clear override path and record why an override was made.

  • Review score distributions at team level so a changing mix of work does not become an individual target.

Frequently asked questions

Common questions about ai pr scoring

What does GitRank use to score a pull request?

GitRank combines a severity base score with a component multiplier and applies your configured eligibility criteria, such as linked issues, tests, and documentation.

Can a manager override an AI PR score?

Yes. AI evaluation is designed to make the reasoning visible, while authorized team members retain the final say over classifications and rewards.

Does AI PR scoring replace code review?

No. GitRank evaluates the impact of merged work for recognition and analysis. It complements, rather than replaces, pre-merge review, testing, and release controls.

Keep exploring GitRank

How GitRank works

See the merge-to-score workflow in detail.

AI-powered PR evaluation

Learn what GitRank evaluates and explains.

Developer leaderboards

Recognize impact through transparent rankings.

Make shipped engineering impact easier to see

Connect GitHub, configure the rules your team values, and start turning merged PRs into explained recognition.

Start free