A GitHub Action that analyzes and displays pull request review statistics to improve team performance and review quality.
Pull Request Stats is a GitHub Action that automatically generates and displays statistics about pull request reviewers. It analyzes review activity across repositories to provide metrics like review time, comment volume, and review frequency, helping teams identify bottlenecks and improve their code review processes.
Development teams and engineering managers using GitHub who want to measure and optimize their code review workflows, track team performance, and make data-driven decisions about reviewer assignments.
It provides a seamless, automated way to gain visibility into review performance directly within GitHub workflows, with privacy-focused design, flexible configuration, and actionable insights that help reduce review cycles and encourage quality feedback.
Github action to print relevant stats about Pull Request reviewers
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Supports stats from a single repository, multiple repositories, or an entire organization using a personal access token, as detailed in the 'token', 'repositories', and 'organization' action inputs.
Publishes results directly into pull request descriptions or comments as formatted tables, outputs data in Markdown or JSON, and offers premium integrations for Slack and Microsoft Teams via webhooks.
Operates statelessly without collecting or storing repository data; all chart data is transmitted via URL parameters, ensuring no external data storage as emphasized in the privacy section.
Generates interactive links to visual charts showing each reviewer's performance over time, helping teams track trends and make informed decisions based on historical data.
Disabling telemetry and using integrations like Slack or Microsoft Teams require a sponsorship starting at $20/month, locking useful functionality behind a paywall as admitted in the premium features section.
Historical charts are hosted on app.flowwer.dev, creating a reliance on an external service that could fail, change, or raise privacy concerns despite the stateless design.
Calculating stats across multiple repositories or organizations mandates a personal access token with 'repo' permissions, which can be error-prone and require additional security management, as noted in troubleshooting.