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Skills/ruvnet/ruflo/agent-code-review-swarm
agent-code-review-swarm logo

agent-code-review-swarm

ruvnet/ruflo
733 installs60K stars
Run it on Hostinger β†’up to 70% off + an extra 10% with code ZACAARON10Free API β†’

Installation

npx skills add https://github.com/ruvnet/ruflo --skill agent-code-review-swarm

Summary

Agent skill for code-review-swarm - invoke with $agent-code-review-swarm

SKILL.md

--- name: code-review-swarm description: Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis tools: mcp__claude-flow__swarm_init, mcp__claude-flow__agent_spawn, mcp__claude-flow__task_orchestrate, Bash, Read, Write, TodoWrite color: blue type: development capabilities:

  • Automated multi-agent code review
  • Security vulnerability analysis
  • Performance bottleneck detection
  • Architecture pattern validation
  • Style and convention enforcement

priority: high hooks: pre: | echo "Starting code-review-swarm..." echo "Initializing multi-agent review system" gh auth status || (echo "GitHub CLI not authenticated" && exit 1) post: | echo "Completed code-review-swarm" echo "Review results posted to GitHub" echo "Quality gates evaluated" ---

Code Review Swarm - Automated Code Review with AI Agents

Overview

Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis.

Core Features

1. Multi-Agent Review System

# Initialize code review swarm with gh CLI
# Get PR details
PR_DATA=$(gh pr view 123 --json files,additions,deletions,title,body)
PR_DIFF=$(gh pr diff 123)

# Initialize swarm with PR context
npx ruv-swarm github review-init \
  --pr 123 \
  --pr-data "$PR_DATA" \
  --diff "$PR_DIFF" \
  --agents "security,performance,style,architecture,accessibility" \
  --depth comprehensive

# Post initial review status
gh pr comment 123 --body "πŸ” Multi-agent code review initiated"

2. Specialized Review Agents

Security Agent
# Security-focused review with gh CLI
# Get changed files
CHANGED_FILES=$(gh pr view 123 --json files --jq '.files[].path')

# Run security review
SECURITY_RESULTS=$(npx ruv-swarm github review-security \
  --pr 123 \
  --files "$CHANGED_FILES" \
  --check "owasp,cve,secrets,permissions" \
  --suggest-fixes)

# Post security findings
if echo "$SECURITY_RESULTS" | grep -q "critical"; then
  # Request changes for critical issues
  gh pr review 123 --request-changes --body "$SECURITY_RESULTS"
  # Add security label
  gh pr edit 123 --add-label "security-review-required"
else
  # Post as comment for non-critical issues
  gh pr comment 123 --body "$SECURITY_RESULTS"
fi
Performance Agent
# Performance analysis
npx ruv-swarm github review-performance \
  --pr 123 \
  --profile "cpu,memory,io" \
  --benchmark-against main \
  --suggest-optimizations
Architecture Agent
# Architecture review
npx ruv-swarm github review-architecture \
  --pr 123 \
  --check "patterns,coupling,cohesion,solid" \
  --visualize-impact \
  --suggest-refactoring

3. Review Configuration

# .github$review-swarm.yml
version: 1
review:
  auto-trigger: true
  required-agents:
    - security
    - performance
    - style
  optional-agents:
    - architecture
    - accessibility
    - i18n
  
  thresholds:
    security: block
    performance: warn
    style: suggest
    
  rules:
    security:
      - no-eval
      - no-hardcoded-secrets
      - proper-auth-checks
    performance:
      - no-n-plus-one
      - efficient-queries
      - proper-caching
    architecture:
      - max-coupling: 5
      - min-cohesion: 0.7
      - follow-patterns

Review Agents

Security Review Agent

// Security checks performed
{
  "checks": [
    "SQL injection vulnerabilities",
    "XSS attack vectors",
    "Authentication bypasses",
    "Authorization flaws",
    "Cryptographic weaknesses",
    "Dependency vulnerabilities",
    "Secret exposure",
    "CORS misconfigurations"
  ],
  "actions": [
    "Block PR on critical issues",
    "Suggest secure alternatives",
    "Add security test cases",
    "Update security documentation"
  ]
}

Performance Review Agent

// Performance analysis
{
  "metrics": [
    "Algorithm complexity",
    "Database query efficiency",
    "Memory allocation patterns",
    "Cache utilization",
    "Network request optimization",
    "Bundle size impact",
    "Render performance"
  ],
  "benchmarks": [
    "Compare with baseline",
    "Load test simulations",
    "Memory leak detection",
    "Bottleneck identification"
  ]
}

Style & Convention Agent

// Style enforcement
{
  "checks": [
    "Code formatting",
    "Naming conventions",
    "Documentation standards",
    "Comment quality",
    "Test coverage",
    "Error handling patterns",
    "Logging standards"
  ],
  "auto-fix": [
    "Formatting issues",
    "Import organization",
    "Trailing whitespace",
    "Simple naming issues"
  ]
}

Architecture Review Agent

// Architecture analysis
{
  "patterns": [
    "Design pattern adherence",
    "SOLID principles",
    "DRY violations",
    "Separation of concerns",
    "Dependency injection",
    "Layer violations",
    "Circular dependencies"
  ],
  "metrics": [
    "Coupling metrics",
    "Cohesion scores",
    "Complexity measures",
    "Maintainability index"
  ]
}

Advanced Review Features

1. Context-Aware Reviews

# Review with full context
npx ruv-swarm github review-context \
  --pr 123 \
  --load-related-prs \
  --analyze-impact \
  --check-breaking-changes

2. Learning from History

# Learn from past reviews
npx ruv-swarm github review-learn \
  --analyze-past-reviews \
  --identify-patterns \
  --improve-suggestions \
  --reduce-false-positives

3. Cross-PR Analysis

# Analyze related PRs together
npx ruv-swarm github review-batch \
  --prs "123,124,125" \
  --check-consistency \
  --verify-integration \
  --combined-impact

Review Automation

Auto-Review on Push

# .github$workflows$auto-review.yml
name: Automated Code Review
on:
  pull_request:
    types: [opened, synchronize]

jobs:
  swarm-review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions$checkout@v3
        with:
          fetch-depth: 0
          
      - name: Setup GitHub CLI
        run: echo "${{ secrets.GITHUB_TOKEN }}" | gh auth login --with-token
          
      - name: Run Review Swarm
        run: |
          # Get PR context with gh CLI
          PR_NUM=${{ github.event.pull_request.number }}
          PR_DATA=$(gh pr view $PR_NUM --json files,title,body,labels)
          
          # Run swarm review
          REVIEW_OUTPUT=$(npx ruv-swarm github review-all \
            --pr $PR_NUM \
            --pr-data "$PR_DATA" \
            --agents "security,performance,style,architecture")
          
          # Post review results
          echo "$REVIEW_OUTPUT" | gh pr review $PR_NUM --comment -F -
          
          # Update PR status
          if echo "$REVIEW_OUTPUT" | grep -q "approved"; then
            gh pr review $PR_NUM --approve
          elif echo "$REVIEW_OUTPUT" | grep -q "changes-requested"; then
            gh pr review $PR_NUM --request-changes -b "See review comments above"
          fi

Review Triggers

// Custom review triggers
{
  "triggers": {
    "high-risk-files": {
      "paths": ["**$auth/**", "**$payment/**"],
      "agents": ["security", "architecture"],
      "depth": "comprehensive"
    },
    "performance-critical": {
      "paths": ["**$api/**", "**$database/**"],
      "agents": ["performance", "database"],
      "benchmarks": true
    },
    "ui-changes": {
      "paths": ["**$components/**", "**$styles/**"],
      "agents": ["accessibility", "style", "i18n"],
      "visual-tests": true
    }
  }
}

Review Comments

Intelligent Comment Generation

# Generate contextual review comments with gh CLI
# Get PR diff with context
PR_DIFF=$(gh pr diff 123 --color never)
PR_FILES=$(gh pr view 123 --json files)

# Generate review comments
COMMENTS=$(npx ruv-swarm github review-comment \
  --pr 123 \
  --diff "$PR_DIFF" \
  --files "$PR_FILES" \
  --style "constructive" \
  --include-examples \
  --suggest-fixes)

# Post comments using gh CLI
echo "$COMMENTS" | jq -c '.[]' | while read -r comment; do
  FILE=$(echo "$comment" | jq -r '.path')
  LINE=$(echo "$comment" | jq -r '.line')
  BODY=$(echo "$comment" | jq -r '.body')
  
  # Create review with inline comments
  gh api \
    --method POST \
    $repos/:owner/:repo$pulls/123$comments \
    -f path="$FILE" \
    -f line="$LINE" \
    -f body="$BODY" \
    -f commit_id="$(gh pr view 123 --json headRefOid -q .headRefOid)"
done

Comment Templates

<!-- Security Issue Template -->
πŸ”’ **Security Issue: [Type]**

**Severity**: πŸ”΄ Critical / 🟑 High / 🟒 Low

**Description**: 
[Clear explanation of the security issue]

**Impact**:
[Potential consequences if not addressed]

**Suggested Fix**:

[Code example of the fix]


**References**:
- [OWASP Guide](link)
- [Security Best Practices](link)

Batch Comment Management

# Manage review comments efficiently
npx ruv-swarm github review-comments \
  --pr 123 \
  --group-by "agent,severity" \
  --summarize \
  --resolve-outdated

Integration with CI/CD

Status Checks

# Required status checks
protection_rules:
  required_status_checks:
    contexts:
      - "review-swarm$security"
      - "review-swarm$performance"
      - "review-swarm$architecture"

Quality Gates

# Define quality gates
npx ruv-swarm github quality-gates \
  --define '{
    "security": {"threshold": "no-critical"},
    "performance": {"regression": "<5%"},
    "coverage": {"minimum": "80%"},
    "architecture": {"complexity": "<10"}
  }'

Review Metrics

# Track review effectiveness
npx ruv-swarm github review-metrics \
  --period 30d \
  --metrics "issues-found,false-positives,fix-rate" \
  --export-dashboard

Best Practices

1. Review Configuration

  • Define clear review criteria
  • Set appropriate thresholds
  • Configure agent specializations
  • Establish override procedures

2. Comment Quality

  • Provide actionable feedback
  • Include code examples
  • Reference documentation
  • Maintain respectful tone

3. Performance

  • Cache analysis results
  • Incremental reviews for large PRs
  • Parallel agent execution
  • Smart comment batching

Advanced Features

1. AI Learning

# Train on your codebase
npx ruv-swarm github review-train \
  --learn-patterns \
  --adapt-to-style \
  --improve-accuracy

2. Custom Review Agents

// Create custom review agent
class CustomReviewAgent {
  async review(pr) {
    const issues = [];
    
    // Custom logic here
    if (await this.checkCustomRule(pr)) {
      issues.push({
        severity: 'warning',
        message: 'Custom rule violation',
        suggestion: 'Fix suggestion'
      });
    }
    
    return issues;
  }
}

3. Review Orchestration

# Orchestrate complex reviews
npx ruv-swarm github review-orchestrate \
  --strategy "risk-based" \
  --allocate-time-budget \
  --prioritize-critical

Examples

Security-Critical PR

# Auth system changes
npx ruv-swarm github review-init \
  --pr 456 \
  --agents "security,authentication,audit" \
  --depth "maximum" \
  --require-security-approval

Performance-Sensitive PR

# Database optimization
npx ruv-swarm github review-init \
  --pr 789 \
  --agents "performance,database,caching" \
  --benchmark \
  --profile

UI Component PR

# New component library
npx ruv-swarm github review-init \
  --pr 321 \
  --agents "accessibility,style,i18n,docs" \
  --visual-regression \
  --component-tests

Monitoring & Analytics

Review Dashboard

# Launch review dashboard
npx ruv-swarm github review-dashboard \
  --real-time \
  --show "agent-activity,issue-trends,fix-rates"

Review Reports

# Generate review reports
npx ruv-swarm github review-report \
  --format "markdown" \
  --include "summary,details,trends" \
  --email-stakeholders

See also: swarm-pr.md, workflow-automation.md

Score

0–100
65/ 100

Grade

C

Popularity17/30

733 installs β€” growing adoption. Source repo has 59,592 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness β€” computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Agent Code Review Swarm skill score badge previewScore badge

Markdown

[![Agent Code Review Swarm skill](https://www.remoteopenclaw.com/skills/ruvnet/ruflo/agent-code-review-swarm/badges/score.svg)](https://www.remoteopenclaw.com/skills/ruvnet/ruflo/agent-code-review-swarm)

HTML

<a href="https://www.remoteopenclaw.com/skills/ruvnet/ruflo/agent-code-review-swarm"><img src="https://www.remoteopenclaw.com/skills/ruvnet/ruflo/agent-code-review-swarm/badges/score.svg" alt="Agent Code Review Swarm skill"/></a>

Agent Code Review Swarm FAQ

How do I install the Agent Code Review Swarm skill?

Run β€œnpx skills add https://github.com/ruvnet/ruflo --skill agent-code-review-swarm” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run β€” no restart or extra configuration needed.

What does the Agent Code Review Swarm skill do?

Agent skill for code-review-swarm - invoke with $agent-code-review-swarm The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Agent Code Review Swarm skill free?

Yes. Agent Code Review Swarm is a free, open-source skill published from ruvnet/ruflo. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Agent Code Review Swarm work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Agent Code Review Swarm works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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Start building free β†’
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