Comprehensive Review Full Review

Use this skill when

• Working on comprehensive review full review tasks or workflows
• Needing guidance, best practices, or checklists for comprehensive review full review

Do not use this skill when

• The task is unrelated to comprehensive review full review
• You need a different domain or tool outside this scope

Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Orchestrate comprehensive multi-dimensional code review using specialized review agents

[Extended thinking: This workflow performs an exhaustive code review by orchestrating multiple specialized agents in sequential phases. Each phase builds upon previous findings to create a comprehensive review that covers code quality, security, performance, testing, documentation, and best practices. The workflow integrates modern AI-assisted review tools, static analysis, security scanning, and automated quality metrics. Results are consolidated into actionable feedback with clear prioritization and remediation guidance. The phased approach ensures thorough coverage while maintaining efficiency through parallel agent execution where appropriate.]

Review Configuration Options

• --security-focus: Prioritize security vulnerabilities and OWASP compliance
• --performance-critical: Emphasize performance bottlenecks and scalability issues
• --tdd-review: Include TDD compliance and test-first verification
• --ai-assisted: Enable AI-powered review tools (Copilot, Codium, Bito)
• --strict-mode: Fail review on any critical issues found
• --metrics-report: Generate detailed quality metrics dashboard
• --framework [name]: Apply framework-specific best practices (React, Spring, Django, etc.)

Phase 1: Code Quality & Architecture Review

Use Task tool to orchestrate quality and architecture agents in parallel:

1A. Code Quality Analysis

• Use Task tool with subagent_type="code-reviewer"
• Prompt: "Perform comprehensive code quality review for: $ARGUMENTS. Analyze code complexity, maintainability index, technical debt, code duplication, naming conventions, and adherence to Clean Code principles. Integrate with SonarQube, CodeQL, and Semgrep for static analysis. Check for code smells, anti-patterns, and violations of SOLID principles. Generate cyclomatic complexity metrics and identify refactoring opportunities."
• Expected output: Quality metrics, code smell inventory, refactoring recommendations
• Context: Initial codebase analysis, no dependencies on other phases

1B. Architecture & Design Review

• Use Task tool with subagent_type="architect-review"
• Prompt: "Review architectural design patterns and structural integrity in: $ARGUMENTS. Evaluate microservices boundaries, API design, database schema, dependency management, and adherence to Domain-Driven Design principles. Check for circular dependencies, inappropriate coupling, missing abstractions, and architectural drift. Verify compliance with enterprise architecture standards and cloud-native patterns."
• Expected output: Architecture assessment, design pattern analysis, structural recommendations
• Context: Runs parallel with code quality analysis

Phase 2: Security & Performance Review

Use Task tool with security and performance agents, incorporating Phase 1 findings:

2A. Security Vulnerability Assessment

• Use Task tool with subagent_type="security-auditor"
• Prompt: "Execute comprehensive security audit on: $ARGUMENTS. Perform OWASP Top 10 analysis, dependency vulnerability scanning with Snyk/Snyk, secrets detection with GitLeaks, input validation review, authentication/authorization assessment, and cryptographic implementation review. Include findings from Phase 1 architecture review: {phase1_architecture_context}. Check for SQL injection, XSS, CSRF, insecure deserialization, and configuration security issues."
• Expected output: Vulnerability report, CVE list, security risk matrix, remediation steps
• Context: Incorporates architectural vulnerabilities identified in Phase 1B

2B. Performance & Scalability Analysis

• Use Task tool with subagent_type="application-performance::performance-engineer"
• Prompt: "Conduct performance analysis and scalability assessment for: $ARGUMENTS. Profile code for CPU/memory hotspots, analyze database query performance, review caching strategies, identify N+1 problems, assess connection pooling, and evaluate asynchronous processing patterns. Consider architectural findings from Phase 1: {phase1_architecture_context}. Check for memory leaks, resource contention, and bottlenecks under load."
• Expected output: Performance metrics, bottleneck analysis, optimization recommendations
• Context: Uses architecture insights to identify systemic performance issues

Phase 3: Testing & Documentation Review

Use Task tool for test and documentation quality assessment:

3A. Test Coverage & Quality Analysis

• Use Task tool with subagent_type="unit-testing::test-automator"
• Prompt: "Evaluate testing strategy and implementation for: $ARGUMENTS. Analyze unit test coverage, integration test completeness, end-to-end test scenarios, test pyramid adherence, and test maintainability. Review test quality metrics including assertion density, test isolation, mock usage, and flakiness. Consider security and performance test requirements from Phase 2: {phase2_security_context}, {phase2_performance_context}. Verify TDD practices if --tdd-review flag is set."
• Expected output: Coverage report, test quality metrics, testing gap analysis
• Context: Incorporates security and performance testing requirements from Phase 2

3B. Documentation & API Specification Review

• Use Task tool with subagent_type="code-documentation::docs-architect"
• Prompt: "Review documentation completeness and quality for: $ARGUMENTS. Assess inline code documentation, API documentation (OpenAPI/Swagger), architecture decision records (ADRs), README completeness, deployment guides, and runbooks. Verify documentation reflects actual implementation based on all previous phase findings: {phase1_context}, {phase2_context}. Check for outdated documentation, missing examples, and unclear explanations."
• Expected output: Documentation coverage report, inconsistency list, improvement recommendations
• Context: Cross-references all previous findings to ensure documentation accuracy

Phase 4: Best Practices & Standards Compliance

Use Task tool to verify framework-specific and industry best practices:

4A. Framework & Language Best Practices

• Use Task tool with subagent_type="framework-migration::legacy-modernizer"
• Prompt: "Verify adherence to framework and language best practices for: $ARGUMENTS. Check modern JavaScript/TypeScript patterns, React hooks best practices, Python PEP compliance, Java enterprise patterns, Go idiomatic code, or framework-specific conventions (based on --framework flag). Review package management, build configuration, environment handling, and deployment practices. Include all quality issues from previous phases: {all_previous_contexts}."
• Expected output: Best practices compliance report, modernization recommendations
• Context: Synthesizes all previous findings for framework-specific guidance

4B. CI/CD & DevOps Practices Review

• Use Task tool with subagent_type="cicd-automation::deployment-engineer"
• Prompt: "Review CI/CD pipeline and DevOps practices for: $ARGUMENTS. Evaluate build automation, test automation integration, deployment strategies (blue-green, canary), infrastructure as code, monitoring/observability setup, and incident response procedures. Assess pipeline security, artifact management, and rollback capabilities. Consider all issues identified in previous phases that impact deployment: {all_critical_issues}."
• Expected output: Pipeline assessment, DevOps maturity evaluation, automation recommendations
• Context: Focuses on operationalizing fixes for all identified issues

Consolidated Report Generation

Compile all phase outputs into comprehensive review report:

Critical Issues (P0 - Must Fix Immediately)

• Security vulnerabilities with CVSS > 7.0
• Data loss or corruption risks
• Authentication/authorization bypasses
• Production stability threats
• Compliance violations (GDPR, PCI DSS, SOC2)

High Priority (P1 - Fix Before Next Release)

• Performance bottlenecks impacting user experience
• Missing critical test coverage
• Architectural anti-patterns causing technical debt
• Outdated dependencies with known vulnerabilities
• Code quality issues affecting maintainability

Medium Priority (P2 - Plan for Next Sprint)

• Non-critical performance optimizations
• Documentation gaps and inconsistencies
• Code refactoring opportunities
• Test quality improvements
• DevOps automation enhancements

Low Priority (P3 - Track in Backlog)

• Style guide violations
• Minor code smell issues
• Nice-to-have documentation updates
• Cosmetic improvements

Success Criteria

Review is considered successful when:

• All critical security vulnerabilities are identified and documented
• Performance bottlenecks are profiled with remediation paths
• Test coverage gaps are mapped with priority recommendations
• Architecture risks are assessed with mitigation strategies
• Documentation reflects actual implementation state
• Framework best practices compliance is verified
• CI/CD pipeline supports safe deployment of reviewed code
• Clear, actionable feedback is provided for all findings
• Metrics dashboard shows improvement trends
• Team has clear prioritized action plan for remediation

Target: $ARGUMENTS

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Cache workflow configurations and automation patterns. Retrieve prior pipeline designs to avoid re-building similar flows from scratch.

# Check for prior workflow/automation context before starting
python3 execution/memory_manager.py auto --query "automation patterns and workflow configurations for Comprehensive Review Full Review"

Storing Results

After completing work, store workflow/automation decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Workflow: automated data pipeline with retry logic, dead-letter queue, and Slack alerts on failure" \
  --type technical --project <project> \
  --tags comprehensive-review-full-review workflow

Multi-Agent Collaboration

Share workflow state with other agents so they can trigger, monitor, or extend the automation.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Workflow automation deployed — pipeline processing 1000+ events/day with 99.9% success rate" \
  --project <project>

Playbook Engine

Combine this skill with others using the Playbook Engine (execution/workflow_engine.py) for guided multi-step automation with progress tracking.