Automate GitHub Pull Request Review with Slack Alerts and Developer Metrics

Introduction

Speed up code reviews and keep your team aligned—without manual overhead. ✅

Trigger Event

When a GitHub pull request is opened or updated (e.g., new commits are pushed), this automation kicks in.

Actions

• First, it checks the branch name against your policy (feature_via_YYYY-MM-DD_N). If the branch format is wrong, it immediately requests changes on the PR and posts a clear Slack alert so the author can fix it fast.

• If the branch is valid, it fetches the PR’s file changes from GitHub and enriches them with relevant TODO/context from your viaSocket Table. That enriched payload is sent to your review service to analyze patterns, test IDs, and quality signals.

• The workflow tallies file-change counts, lets the analyzer finish (brief delay), and stores short-term context in Workspace Memory to guide the next steps.

• Based on the analyzer’s decision and rating, it produces one of two outcomes:

  • Approve: It submits an approval on GitHub automatically.
  • Reject: It compiles a concise Markdown summary with numbered reasons for changes.

• If required test IDs are detected, the QA channel is notified on Slack so they can validate quickly. If the decision is unclear, the author gets a direct Slack message with what to do next.

• Developer metrics are kept up to date in your viaSocket Table:

  • Looks up the developer’s record for this task or PR.
  • If rejected, it increments the rejection count; if approved, it updates review notes and rating.
  • Calculates a final score using rating, decision, and rejection history, then saves everything for easy reporting.

• Finally, it updates any task/issue record with the AI review summary and cleans temporary memory so your workspace stays tidy.

Benefits

• Enforces branch naming rules automatically
• Faster approvals when code is clean; instant, clear feedback when not
• Slack alerts to authors and QA keep everyone in the loop
• Stores decisions, ratings, and scores for developer analytics
• Reduces manual review time and context switching
• Consistent, auditable PR reviews across teams