GitHub PR analytics that find code review bottlenecks

GitQuick is pull request analytics for engineering managers, platform teams, and tech leads. It reads GitHub pull-request metadata — not source code — and surfaces PR review metrics that show where delivery stalls: time to first review, approval-to-merge time, PR throughput, reviewer workload, PR size, P90 latency, merges without review, and bot versus human review activity.

GitHub PR analytics for engineering teams. Read-only GitHub App.

Key signals

• Review Latency — PRs waiting too long for first review or approval, with p90 tails flagged separately from medians.
• Merge Pipeline Friction — Approved PRs stalling before merge.
• Backlog / Throughput Imbalance — More PRs opened than merged each week.
• Review Quality Risk — High merged-without-review rate or bot-dominated approvals.
• PR Size Risk — PRs too large for humans to review effectively.
• Dev Cycle Delay — Work incubating locally too long before opening a PR.

Pull request analytics and PR review metrics

• Deep Metrics Dashboard — Time to first review, approval latency, approval-to-merge, throughput, PR size, bot vs human reviews, reviewer load, and distributions.
• AI Executive Reports (coming soon) — LLM-written summaries in Executive and Engineering Manager modes, rolling out to early-access users.
• Repo Groups & Scoped Views — Custom repo groups; every metric recalculates for the selected scope.
• Language Breakdown — All metrics segmented by primary language.