Track impact trends
Analyze score, severity, and component patterns across the work that reached the main branch.
GitRank gives teams a practical view of the pull requests that have already shipped: their impact, component, eligibility, review timing, and contribution patterns.
Use one PR-level record for engineering conversations that otherwise require jumping between GitHub, spreadsheets, and separate reporting tools.
A volume chart can tell you that a team merged more PRs. It cannot tell you which changes addressed critical issues, where quality risk is recurring, or whether review delays are stopping valuable work.
Analyze score, severity, and component patterns across the work that reached the main branch.
Use review timing and cycle data to identify PRs that are waiting, moving, or repeatedly returning for changes.
See where higher-severity fixes cluster so teams can investigate product hotspots early.
Install the GitHub App, select repositories, and let GitRank receive merged pull request events automatically.
GitRank reads the merged diff, linked issues, component rules, and eligibility requirements before producing an explanation.
Scores, summaries, and trends feed leaderboards, review workflows, bonus programs, and team discussions without relying on raw activity counts.
Review trends by team and component before drawing conclusions about an individual.
Pair speed metrics with quality and rework context so faster is not automatically considered better.
Link recurring insights to a concrete workflow change, owner, or retrospective action.
GitRank uses merged pull request information, diffs, linked issues, repository configuration, and review activity to evaluate impact and delivery patterns.
Yes. Review velocity analytics surface timing and responsiveness signals so teams can investigate waiting time and review load.
No. GitRank also posts explained evaluations, powers recognition and bounty programs, and produces product-oriented summaries from merged work.
Connect GitHub, configure the rules your team values, and start turning merged PRs into explained recognition.
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