Code Review Orchestration Patterns

VerifiedSafe

Orchestrates multi-agent code reviews by fanning out analysis across parallel dimensions (quality, logic, security, performance) then synthesizing prioritized feedback. Helps streamline thorough PR reviews, security audits, and architecture evaluations.

Sby Skills Guide Bot
DevelopmentIntermediate
406/2/2026
Claude Code
#code-review#orchestration#security-audit#performance-review#architecture-review

Recommended for

Our review

This skill orchestrates multi-dimensional code reviews in parallel, generating unified and prioritized feedback for pull requests, security audits, performance reviews, and architecture reviews.

Strengths

  • Parallel analysis across multiple dimensions (code quality, security, performance, architecture)
  • Unified synthesis with prioritized findings
  • Supports multiple review types (PR, security, performance, architecture)
  • Scalable through specialized sub-agents

Limitations

  • Requires careful coordination of sub-agents
  • May produce overlapping results between dimensions
  • Depends on model quality for each dimension
When to use it

Use this skill for comprehensive code reviews that require multi-faceted analysis and structured feedback.

When not to use it

Avoid for trivial changes or minor modifications that do not warrant extensive orchestration.

Security analysis

Safe
Quality score90/100

The skill describes code review orchestration patterns using task management and subagents. It contains no instructions for destructive, exfiltrating, or obfuscated actions. No commands like curl, sh, rm, or secret handling are present. The bash examples use 'npx cc-mirror tasks create' for task management, which is not inherently dangerous.

No concerns found

Examples

Pull Request Review
Review PR #123
Security Audit
Security audit the authentication module
Performance Review
Find performance bottlenecks

Code Review Orchestration Patterns

┌─────────────────────────────────────────────────────────────┐
│                                                             │
│   Reviews should be thorough, fast, and actionable.         │
│   Parallel analysis. Unified feedback. Clear priorities.    │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Load when: PR review, security audit, performance review, architecture review, pre-merge validation Common patterns: Multi-Dimensional Analysis, OWASP-Parallel, Layer-by-Layer

Table of Contents

  1. Pull Request Review
  2. Security Audit
  3. Performance Review
  4. Architecture Review
  5. Pre-merge Validation

Pull Request Review

Pattern: Multi-Dimensional Analysis

User Request: "Review PR #123"

Phase 1: FAN-OUT (Parallel analysis dimensions)
├─ Explore agent: Understand PR context, related issues
├─ Agent A: Code quality analysis (style, patterns, DRY)
├─ Agent B: Logic correctness (edge cases, error handling)
├─ Agent C: Security implications
└─ Agent D: Performance implications

Phase 2: REDUCE (Synthesize)
└─ General-purpose agent: Aggregate findings, prioritize, format review

Implementation:

# All in single message for parallelism (opus for reviews - critical thinking)
Task(subagent_type="Explore", prompt="Fetch PR #123 details, understand context and related issues",
     model="haiku", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Review code quality: patterns, readability, maintainability",
     model="opus", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Review logic: correctness, edge cases, error handling",
     model="opus", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Review security: injection, auth, data exposure",
     model="opus", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Review performance: complexity, queries, memory",
     model="opus", run_in_background=True)

Security Audit

Pattern: OWASP-Parallel

User Request: "Security audit the authentication module"

Phase 1: FAN-OUT (OWASP categories in parallel)
├─ Agent A: Injection vulnerabilities (SQL, command, XSS)
├─ Agent B: Authentication/session issues
├─ Agent C: Access control problems
├─ Agent D: Cryptographic weaknesses
├─ Agent E: Data exposure risks
└─ Agent F: Security misconfiguration

Phase 2: REDUCE
└─ General-purpose agent: Risk-ranked findings with remediation

Pattern: Attack Surface Mapping

Phase 1: EXPLORE
└─ Explore agent: Map all entry points (APIs, forms, file uploads)

Phase 2: FAN-OUT (Per entry point)
├─ Agent per entry point: Analyze input validation, sanitization

Phase 3: PIPELINE
└─ General-purpose agent: Threat model, prioritized vulnerabilities

Performance Review

Pattern: Layer-by-Layer

User Request: "Find performance bottlenecks"

Phase 1: FAN-OUT (Analyze each layer)
├─ Agent A: Database queries (N+1, missing indexes, slow queries)
├─ Agent B: API layer (response times, payload sizes)
├─ Agent C: Frontend (bundle size, render performance)
└─ Agent D: Infrastructure (caching, connection pooling)

Phase 2: REDUCE
└─ General-purpose agent: Prioritized optimization roadmap

Pattern: Complexity Audit

Phase 1: MAP
└─ Explore agent: Find all functions, measure complexity

Phase 2: FAN-OUT (High complexity functions)
├─ Agent A: Analyze function X, suggest optimizations
├─ Agent B: Analyze function Y, suggest optimizations
└─ Agent C: Analyze function Z, suggest optimizations

Architecture Review

Pattern: Multi-Stakeholder

User Request: "Review system architecture"

Phase 1: FAN-OUT (Perspectives)
├─ Agent A: Scalability assessment
├─ Agent B: Maintainability assessment
├─ Agent C: Security architecture
├─ Agent D: Cost efficiency
└─ Agent E: Developer experience

Phase 2: REDUCE
└─ Plan agent: Synthesize into architecture decision record

Pattern: Dependency Analysis

Phase 1: EXPLORE
└─ Explore agent: Map all module dependencies

Phase 2: FAN-OUT
├─ Agent A: Identify circular dependencies
├─ Agent B: Find coupling hotspots
└─ Agent C: Assess abstraction boundaries

Phase 3: PIPELINE
└─ Plan agent: Recommend architectural improvements

Pre-merge Validation

Pattern: Comprehensive Gate

User Request: "Validate PR ready for merge"

Phase 1: FAN-OUT (All checks in parallel)
├─ Background agent: Run full test suite
├─ Agent A: Verify all review comments addressed
├─ Agent B: Check for merge conflicts
├─ Agent C: Validate documentation updated
└─ Agent D: Confirm CI checks passing

Phase 2: REDUCE
└─ General-purpose agent: Go/no-go recommendation with blockers

Review Output Formats

Structured Review Template

## Summary

[1-2 sentence overview]

## Risk Assessment

- **Security**: Low/Medium/High
- **Performance**: Low/Medium/High
- **Breaking Changes**: Yes/No

## Must Fix (Blocking)

1. [Critical issue with line reference]

## Should Fix (Non-blocking)

1. [Important improvement]

## Consider (Optional)

1. [Nice-to-have suggestion]

## Positive Notes

- [What was done well]

Task Management for Reviews

For comprehensive reviews, create parallel analysis tasks:

# Create review tasks (can run in parallel)
npx cc-mirror tasks create --subject "Analyze PR context" --description "Understand changes, related issues..."
npx cc-mirror tasks create --subject "Review code quality" --description "Patterns, readability, maintainability..."
npx cc-mirror tasks create --subject "Check security" --description "Injection, auth, data exposure..."
npx cc-mirror tasks create --subject "Assess performance" --description "Complexity, queries, memory..."
npx cc-mirror tasks create --subject "Synthesize review" --description "Aggregate findings into review..."

# Synthesis blocked by analysis tasks
npx cc-mirror tasks update 5 --add-blocked-by 1,2,3,4
# Spawn parallel agents for analysis (opus for reviews - critical thinking)
Task(subagent_type="Explore", prompt="Task 1: Analyze PR context...",
     model="haiku", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Task 2: Review code quality...",
     model="opus", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Task 3: Check security...",
     model="opus", run_in_background=True)
Task(subagent_type="general-purpose", prompt="Task 4: Assess performance...",
     model="opus", run_in_background=True)

─── ◈ Code Review ───────────────────────
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