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How to Handle Pull Requests with Many Code Review Comments
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How to Handle Pull Requests with Many Code Review Comments

When a pull request receives dozens or hundreds of code review comments (especially from automated tools like CodeRabbit), it can feel overwhelming. CodeFrog provides a streamlined workflow to help you efficiently process and address all feedback.

Overview

The key to handling large PRs is a two-phase approach:

  1. Manual Review First: Review and handle critical/tough issues independently
  2. Bulk Import & AI Assistance: Import remaining issues to markdown for AI agent assistance

This workflow ensures you address important issues with proper care while efficiently handling routine feedback.

Step-by-Step Workflow

Phase 1: Manual Review of Critical Issues

⚠️ Critical Step - Do Not Skip

Before importing anything, manually review all PR comments to identify issues that need individual attention:

  1. Open the PR in CodeFrog:
    • Navigate to the GitHub tab
    • Select the repository and pull request
    • Review all comments in the PR view
  2. Identify Critical/Tough Issues:
    • Security vulnerabilities - These need careful review
    • Architectural changes - Major design decisions
    • Complex logic bugs - Issues requiring deep understanding
    • Performance issues - Optimization opportunities
    • Breaking changes - Changes that affect other code
    • Context-dependent issues - Comments requiring domain knowledge
  3. Handle Critical Issues First:
    • Fix each critical issue individually
    • Test thoroughly after each fix
    • Commit separately with clear commit messages
    • Mark as resolved in GitHub if applicable
  4. Note Simple/Routine Issues:
    • Style fixes (formatting, naming conventions)
    • Simple null checks
    • Minor refactoring
    • Simple validation additions
    • Documentation updates

Why this matters: Critical issues require human judgment and context. Bulk processing them can lead to incorrect fixes or missed important details.

Phase 2: Import All Issues to Markdown

Once you’ve handled the critical issues, use CodeFrog’s GitHub tab to import all remaining comments into a markdown file:

  1. Navigate to GitHub Tab:
    • Open CodeFrog
    • Go to the GitHub tab (in the navigation menu)
    • Select your repository
    • Click on the pull request with many comments
  2. Review the PR Import Banner:
    • At the top of the PR view, you’ll see the PR Import Banner
    • It shows:
      • Total number of unresolved comments
      • Number of importable comments (those with AI summaries)
      • Number of complex comments (must be handled on web)
  3. Import All Comments:
    • Click “Import Importable Comments” to import all comments with AI summaries
    • Or use “Import First 20 Comments” or “Import First 50 Comments” for batch processing
    • Comments are automatically imported as tasks with format: PR#{pr} Comment #{id}: {description}
    • File paths and line numbers are included automatically
  4. Export to Markdown:
    • After importing, you’ll be prompted to export immediately
    • Or navigate to the Tasks screen (🤖 Task Manager icon)
    • Click the Export Tasks to Markdown button (download icon) in the upper right
    • Choose your export format:
      • Augment Code format: For automated import into Augment Code
      • Simple text format: For pasting into other AI agents like Cursor
  5. Use with AI Agents:
    • Open the exported markdown file
    • Copy the contents
    • Paste into your AI agent of choice (Cursor, ChatGPT, Claude, etc.)
    • The AI agent can help you:
      • Prioritize remaining issues
      • Generate fixes for routine issues
      • Suggest code improvements
      • Create a plan for addressing all comments

Best Practices

Triage Strategy

Handle Individually:

Bulk Process:

Import Strategy

  1. Start Small: Use “Import First 20 Comments” to test the workflow
  2. Review Imported Tasks: Check that tasks are formatted correctly
  3. Export Early: Export to markdown after each batch to avoid losing work
  4. Clear Between PRs: Clear your task list before importing a new PR

AI Agent Workflow

When pasting into AI agents:

  1. Provide Context: Include relevant code snippets or file paths
  2. Ask for Prioritization: Have the AI suggest which issues to tackle first
  3. Request Fixes: Ask for code fixes for routine issues
  4. Review AI Suggestions: Always review AI-generated fixes before applying
  5. Test Thoroughly: Test all fixes, even AI-generated ones

Example Workflow

Scenario: PR with 150 CodeRabbit Comments

  1. Manual Review (30 minutes):
    • Review all 150 comments
    • Identify 15 critical issues (security, architecture)
    • Fix 15 critical issues individually
    • Commit each fix separately
  2. Bulk Import (5 minutes):
    • Import remaining 135 comments via GitHub tab
    • Export to markdown format
    • Clear task list
  3. AI Assistance (20 minutes):
    • Paste markdown into Cursor or other AI agent
    • Have AI prioritize remaining issues
    • Generate fixes for routine issues
    • Review and apply fixes
  4. Final Review (10 minutes):
    • Test all changes
    • Verify all comments are addressed
    • Update PR with status

Total Time: ~65 minutes vs. hours of manual work

Tips for Large PRs

Organization

Efficiency

Quality

Troubleshooting

Import Issues

Export Issues

AI Agent Issues

Summary

Handling PRs with many comments doesn’t have to be overwhelming:

  1. ✅ Review manually first - Identify and fix critical issues
  2. ✅ Import to CodeFrog - Use the GitHub tab to import all comments
  3. ✅ Export to markdown - Create a markdown file from the Tasks screen
  4. ✅ Use AI agents - Paste markdown into Cursor or other AI tools
  5. ✅ Review and test - Always review AI suggestions before applying

This workflow combines human judgment for critical issues with AI efficiency for routine feedback, making large PRs manageable.