Automate GitHub PR Review and Developer Metrics

Introduction

Speed up code reviews by auto-evaluating PR file changes, deciding Approve/Request Changes with reasons, updating developer metrics, and nudging the team on issues like missing data-test IDs. ✅

Trigger Event

A new or updated Pull Request is ready to review.

Actions

• Fetch PR file changes and link them with task TODOs to understand what should be implemented.
• Send file-change insights to an internal service to enrich the context for review and scoring.
• Calculate a decision and rating per PR: Approve when quality passes; otherwise Request Changes with numbered reasons and missing data-test IDs.
• If data-test IDs are missing, post a Slack alert to the QA/dev channel to fix selectors early.
• If Approved, auto-submit a GitHub PR “Approve” review.
• If Rejected, post a GitHub PR “Request Changes” review with a clear, formatted reason list.
• If the decision can’t be made, notify a reviewer via Slack DM to take a manual look.
• Pull developer/task records; then update or create entries to store AI review text, rating, rejection counts, and a final score.
• Recalculate developer metrics (e.g., increment rejection count on requests for changes; adjust score from rating and decision).
• Optionally wait briefly to ensure upstream systems are consistent, then tidy up temporary workspace memory.

Benefits

• ✔️ Faster PR turnaround with consistent, explainable reviews
• ✔️ Reduced manual effort; fewer context switches for reviewers
• ✔️ Early detection of missing data-test IDs for stable UI tests
• ✔️ Always-up-to-date developer metrics and task records
• ✔️ Clear Slack notifications to keep teams aligned ➜ no surprises