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This skill should be used when performing exhaustive code reviews using multi-agent analysis, ultra-thinking, and Git worktrees for deep local inspection. It applies to PR reviews, branch comparisons, and comprehensive code quality assessments.

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SKILL.md

name workflows-review
description This skill should be used when performing exhaustive code reviews using multi-agent analysis, ultra-thinking, and Git worktrees for deep local inspection. It applies to PR reviews, branch comparisons, and comprehensive code quality assessments.

Review Workflow

Perform exhaustive code reviews using multi-agent analysis, ultra-thinking, and Git worktrees for deep local inspection.

Role

Senior Code Review Architect with expertise in security, performance, architecture, and quality assurance.

Prerequisites

  • Git repository with GitHub CLI (gh) installed and authenticated
  • Clean main/master branch
  • Proper permissions to create worktrees and access the repository
  • For document reviews: Path to a markdown file or document

Workflow

1. Determine Review Target & Setup

First, determine the review target type and set up the code for analysis.

Immediate Actions:

  • Determine review type: PR number (numeric), GitHub URL, file path (.md), or current branch
  • Check current git branch
  • If ALREADY on the PR branch → proceed with analysis on current branch
  • If DIFFERENT branch → use @skill/git-worktree for isolated analysis
  • Fetch PR metadata using gh pr view --json for title, body, files, linked issues
  • Set up language-specific analysis tools
  • Prepare security scanning environment
  • Ensure the correct branch is checked out (use gh pr checkout if needed)

Ensure the code is ready for analysis before proceeding.

2. Parallel Agent Reviews

Spawn sub-agents in parallel for comprehensive review. Each sub-agent should focus on a specific aspect of the code.

Core Review Agents (run all in parallel):

  1. Spawn a sub-agent to review Rails conventions using @guidance/review/kieran-rails-reviewer
  2. Spawn a sub-agent to review DHH-style Rails patterns using @guidance/review/dhh-rails-reviewer
  3. If Turbo is used: Spawn a sub-agent for Turbo expertise using @guidance/review/rails-turbo-expert
  4. Spawn a sub-agent to analyze git history using @guidance/review/git-history-analyzer
  5. Spawn a sub-agent to investigate dependencies using @guidance/review/dependency-detective
  6. Spawn a sub-agent for pattern recognition using @guidance/review/pattern-recognition-specialist
  7. Spawn a sub-agent for architecture review using @guidance/review/architecture-strategist
  8. Spawn a sub-agent for code philosophy using @guidance/review/code-philosopher
  9. Spawn a sub-agent for security analysis using @guidance/review/security-sentinel
  10. Spawn a sub-agent for performance review using @guidance/review/performance-oracle
  11. Spawn a sub-agent for DevOps concerns using @guidance/review/devops-harmony-analyst
  12. Spawn a sub-agent for data integrity using @guidance/review/data-integrity-guardian
  13. Spawn a sub-agent to verify agent-accessibility using @guidance/review/agent-native-reviewer

3. Conditional Agents

Run these agents ONLY when the PR matches specific criteria:

If PR contains database migrations (db/migrate/*.rb) or data backfills:

  1. Spawn a sub-agent using @guidance/review/data-migration-expert to validate ID mappings, check for swapped values, verify rollback safety
  2. Spawn a sub-agent using @guidance/review/deployment-verification-agent to create Go/No-Go deployment checklist with SQL verification queries

Trigger conditions:

  • PR includes files matching db/migrate/*.rb
  • PR modifies columns that store IDs, enums, or mappings
  • PR includes data backfill scripts or rake tasks
  • PR changes how data is read/written
  • PR title/body mentions: migration, backfill, data transformation, ID mapping

4. Ultra-Thinking Deep Dive

For each phase, spend maximum cognitive effort. Think step by step. Consider all angles. Question assumptions.

Stakeholder Perspective Analysis

  1. Developer Perspective

    • How easy is this to understand and modify?
    • Are the APIs intuitive?
    • Is debugging straightforward?
    • Can this be tested easily?
  2. Operations Perspective

    • How to deploy this safely?
    • What metrics and logs are available?
    • How to troubleshoot issues?
    • What are the resource requirements?
  3. End User Perspective

    • Is the feature intuitive?
    • Are error messages helpful?
    • Is performance acceptable?
    • Does it solve the problem?
  4. Security Team Perspective

    • What's the attack surface?
    • Are there compliance requirements?
    • How is data protected?
    • What are the audit capabilities?
  5. Business Perspective

    • What's the ROI?
    • Are there legal/compliance risks?
    • How does this affect time-to-market?
    • What's the total cost of ownership?

Scenario Exploration

  • Happy Path: Normal operation with valid inputs
  • Invalid Inputs: Null, empty, malformed data
  • Boundary Conditions: Min/max values, empty collections
  • Concurrent Access: Race conditions, deadlocks
  • Scale Testing: 10x, 100x, 1000x normal load
  • Network Issues: Timeouts, partial failures
  • Resource Exhaustion: Memory, disk, connections
  • Security Attacks: Injection, overflow, DoS
  • Data Corruption: Partial writes, inconsistency
  • Cascading Failures: Downstream service issues

5. Multi-Angle Review Perspectives

Technical Excellence:

  • Code craftsmanship evaluation
  • Engineering best practices
  • Technical documentation quality
  • Tooling and automation assessment

Business Value:

  • Feature completeness validation
  • Performance impact on users
  • Cost-benefit analysis
  • Time-to-market considerations

Risk Management:

  • Security risk assessment
  • Operational risk evaluation
  • Compliance risk verification
  • Technical debt accumulation

Team Dynamics:

  • Code review etiquette
  • Knowledge sharing effectiveness
  • Collaboration patterns
  • Mentoring opportunities

6. Simplification Review

Spawn a sub-agent using @guidance/review/code-simplicity-reviewer to identify simplification opportunities.

7. Findings Synthesis and Todo Creation

ALL findings MUST be stored in the .opencode/todos/ directory. Create todo files immediately after synthesis.

Step 1: Synthesize All Findings

  • Collect findings from all parallel agents
  • Categorize by type: security, performance, architecture, quality, etc.
  • Assign severity levels: 🔴 CRITICAL (P1), 🟡 IMPORTANT (P2), 🔵 NICE-TO-HAVE (P3)
  • Remove duplicate or overlapping findings
  • Estimate effort for each finding (Small/Medium/Large)

Step 2: Create Todo Files

Use @skill/file-todos for structured todo management. Create todo files for ALL findings immediately.

For large PRs with 15+ findings: Spawn sub-agents in parallel to create finding files simultaneously.

File naming convention:

{issue_id}-{status}-{priority}-{description}.md

Examples:
- 001-pending-p1-security-vulnerability.md
- 002-pending-p2-performance-optimization.md
- 003-pending-p3-code-cleanup.md

Status values:

  • pending - New findings, needs triage/decision
  • ready - Approved, ready to work
  • complete - Work finished

Priority values:

  • p1 - Critical (blocks merge, security/data issues)
  • p2 - Important (should fix, architectural/performance)
  • p3 - Nice-to-have (enhancements, cleanup)

Tagging: Always add code-review tag, plus: security, performance, architecture, rails, quality, etc.

Step 3: Summary Report

After creating all todo files, present:

## ✅ Code Review Complete

**Review Target:** PR #XXXX - [PR Title]
**Branch:** [branch-name]

### Findings Summary:
- **Total Findings:** [X]
- **🔴 CRITICAL (P1):** [count] - BLOCKS MERGE
- **🟡 IMPORTANT (P2):** [count] - Should Fix
- **🔵 NICE-TO-HAVE (P3):** [count] - Enhancements

### Created Todo Files:

**P1 - Critical (BLOCKS MERGE):**
- `001-pending-p1-{finding}.md` - {description}

**P2 - Important:**
- `003-pending-p2-{finding}.md` - {description}

**P3 - Nice-to-Have:**
- `005-pending-p3-{finding}.md` - {description}

### Next Steps:
1. Address P1 Findings: CRITICAL - must be fixed before merge
2. Triage all todos in `.opencode/todos/`
3. Work on approved todos using @workflows/work
4. Track progress by updating todo status

8. End-to-End Testing (Optional)

After presenting the Summary Report, offer appropriate testing based on project type:

Detect project type from PR files:

  • iOS/macOS: *.xcodeproj, *.xcworkspace, Package.swift
  • Web: Gemfile, package.json, app/views/*, *.html.*
  • Hybrid: Both iOS and web files

For Web Projects: Offer to spawn a sub-agent for Playwright browser tests on affected pages.

For iOS Projects: Offer to spawn a sub-agent for Xcode simulator tests.

For Hybrid Projects: Offer web only, iOS only, or both.

Important: P1 Findings Block Merge

Any 🔴 P1 (CRITICAL) findings must be addressed before merging the PR. Present these prominently and ensure resolution before accepting the PR.

Related Workflows

  • @workflows/plan - Create implementation plans
  • @workflows/work - Execute work items systematically
  • @workflows/compound - Document solved problems
  • @skill/file-todos - Structured todo management
  • @skill/git-worktree - Isolated worktree management