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managing-coderabbit

Use when working with Coderabbit — codeRabbit AI code review management including automated review comments, auto-suggestions, review customization, and learning from feedback. Use when configuring CodeRabbit for AI-assisted code review, custom review rules, and automated suggestion workflows.

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Managing CodeRabbit

Overview

Manage CodeRabbit AI-powered code review, including automated review comments, contextual suggestions, review customization, and feedback learning to improve review quality over time.

Key Capabilities

  • Automatically review PRs with AI-generated comments and suggestions
  • Configure review focus areas (security, performance, style, bugs)
  • Customize review rules and coding standards
  • Learn from reviewer feedback to reduce false positives
  • Generate PR summaries and walkthrough comments
  • Integrate with GitHub, GitLab, and Azure DevOps

Workflow

1 — Review Configuration

REVIEW SETTINGS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[ ] Review scope:
    [ ] All PRs automatically
    [ ] PRs with @coderabbitai mention
    [ ] PRs targeting specific branches: ___
[ ] Review focus areas:
    [ ] Bug detection
    [ ] Security vulnerabilities
    [ ] Performance issues
    [ ] Code style and best practices
    [ ] Error handling
    [ ] Documentation completeness
[ ] Review depth: superficial / standard / thorough

2 — Custom Instructions

CUSTOM REVIEW RULES (.coderabbit.yaml)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
reviews:
  profile: assertive / chill
  path_instructions:
    - path: "src/api/**"
      instructions: |
        Review for REST API best practices.
        Check error handling and status codes.
        Verify input validation.
    - path: "src/db/**"
      instructions: |
        Check for SQL injection risks.
        Verify index usage for queries.
        Review transaction handling.
  auto_review:
    enabled: true
    ignore_title_keywords:
      - "WIP"
      - "DO NOT MERGE"
    drafts: false

3 — Feedback Learning

FEEDBACK CONFIGURATION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[ ] Learn from resolved/dismissed comments: YES / NO
[ ] Thumbs up/down feedback tracking: YES / NO
[ ] Suppress repeated false positives: YES / NO
[ ] Custom knowledge base: YES / NO
[ ] Team-specific review patterns: YES / NO

Common Operations

Review Analytics

Track AI review accuracy, accepted suggestions, and false positive rates.

Rule Tuning

Adjust custom instructions based on feedback patterns to improve review quality.

Incremental Reviews

Trigger re-review on updated PRs analyzing only the new changes.

Troubleshooting

IssueCauseFix
Too many commentsReview profile too assertiveSwitch to "chill" profile or add path exclusions
Irrelevant suggestionsMissing contextAdd path-specific instructions in .coderabbit.yaml
Review not triggeredDraft PR or WIP titleRemove WIP keyword or enable draft review
Slow review responseLarge diffExclude generated files and vendor directories

Output Format

Present results as a structured report:

Managing Coderabbit Report
══════════════════════════
Resources discovered: [count]

Resource       Status    Key Metric    Issues
──────────────────────────────────────────────
[name]         [ok/warn] [value]       [findings]

Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]

Target ≤50 lines of output. Use tables for multi-resource comparisons.

Anti-Hallucination Rules

  1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
  2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
  3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
  4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
  5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

ShortcutCounterWhy
"I'll skip discovery and check known resources"Always run Phase 1 discovery firstResource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"Follow the full discovery → analysis flowQuick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"Audit configuration explicitlyDefaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"Always check relevant metrics when availableAPI/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"Try the command and report the actual errorAssumed permission failures prevent useful investigation; actual errors are informative

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