Optimize CodeRabbit API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for CodeRabbit integrations. Trigger with phrases like "coderabbit performance", "optimize coderabbit", "coderabbit latency", "coderabbit caching", "coderabbit slow", "coderabbit batch".
From coderabbit-packnpx claudepluginhub nickloveinvesting/nick-love-plugins --plugin coderabbit-packThis skill is limited to using the following tools:
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Details PluginEval's skill quality evaluation: 3 layers (static, LLM judge), 10 dimensions, rubrics, formulas, anti-patterns, badges. Use to interpret scores, improve triggering, calibrate thresholds.
Optimize CodeRabbit review speed, relevance, and developer workflow integration. CodeRabbit reviews typically take 2-10 minutes depending on PR size, with large PRs (1000+ lines) taking up to 15 minutes.
.coderabbit.yaml configuration file in repositories# PR size directly impacts review speed and quality
size_guidelines:
small: # <200 lines changed
review_time: "2-3 minutes"
quality: "High - focused, actionable comments"
medium: # 200-500 lines
review_time: "3-7 minutes"
quality: "Good - may miss nuanced issues"
large: # 500-1000 lines
review_time: "7-12 minutes"
quality: "Moderate - broad strokes only"
huge: # 1000+ lines
review_time: "12-15+ minutes"
quality: "Low - too much context to process well"
# Best practice: enforce PR size limits with CI checks
# max_lines_changed: 500
# .coderabbit.yaml - Give context so reviews are actionable
reviews:
path_instructions:
- path: "src/api/**"
instructions: |
Check for: proper error handling, input validation, auth middleware.
Ignore: logging format, import order.
- path: "src/components/**"
instructions: |
Check for: accessibility (aria labels), performance (no inline styles).
Ignore: CSS naming conventions (handled by linter).
- path: "tests/**"
instructions: |
Check for: assertion completeness, edge cases.
Ignore: test structure (handled by testing framework conventions).
# .coderabbit.yaml - Only re-review changed files on push
reviews:
auto_review:
enabled: true
incremental: true # Re-review only changed files on new pushes
drafts: false # Skip draft PRs (work in progress)
base_branches: [main, develop] # Only PRs targeting these branches
# .coderabbit.yaml - Skip files that don't benefit from AI review
reviews:
auto_review:
ignore_paths:
- "**/*.lock" # Package lock files
- "**/*.snap" # Test snapshots
- "**/*.generated.*" # Generated code
- "**/*.min.js" # Minified files
- "**/vendor/**" # Third-party code
- "**/__mocks__/**" # Test mocks
- "**/fixtures/**" # Test fixtures
ignore_title_keywords:
- "WIP"
- "DO NOT MERGE"
- "chore: bump"
# Match review aggressiveness to team preferences
profiles:
chill: # Few comments, only major issues
best_for: "Senior teams, high-trust environments"
comment_count: "1-3 per PR"
assertive: # Balanced signal-to-noise
best_for: "Most teams (recommended default)"
comment_count: "3-8 per PR"
nitpicky: # Detailed comments on style and best practices
best_for: "Junior teams, onboarding, compliance-critical"
comment_count: "8-15 per PR"
warning: "May cause review fatigue if team isn't expecting it"
| Issue | Cause | Solution |
|---|---|---|
| Review takes 15+ minutes | PR too large (1000+ lines) | Split into smaller PRs |
| Too many irrelevant comments | No path_instructions configured | Add context-specific instructions |
| Reviews on generated files | No ignore_paths configured | Add generated file patterns to exclusions |
| Team ignoring reviews | Profile too nitpicky | Switch to assertive or chill profile |
Basic usage: Apply coderabbit performance tuning to a standard project setup with default configuration options.
Advanced scenario: Customize coderabbit performance tuning for production environments with multiple constraints and team-specific requirements.