ruvnet/ruflo/.agents/skills/agent-code-review-swarm/SKILL.md
agent-code-review-swarm
Agent skill for code-review-swarm - invoke with $agent-code-review-swarm
- Source repository stars
- 66,999
- Declared platforms
- 0
- Static risk flags
- 1
- Last source update
- 2026-08-04
- Source checked
- 2026-08-04
Decision brief
What it does—and where it fits
Agent skill for code-review-swarm - invoke with $agent-code-review-swarm
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/ruvnet/ruflo --skill ".agents/skills/agent-code-review-swarm"Inspect the Agent Skill "agent-code-review-swarm" from https://github.com/ruvnet/ruflo/blob/913f9eaedee92627950544424e50339feaf98271/.agents/skills/agent-code-review-swarm/SKILL.md at commit 913f9eaedee92627950544424e50339feaf98271. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
1. Multi-Agent Review System
Review the “1. Multi-Agent Review System” section in the pinned source before continuing.
Review and apply the “1. Multi-Agent Review System” source section. - 02
Initialize code review swarm with gh CLI
Review the “Initialize code review swarm with gh CLI” section in the pinned source before continuing.
Review and apply the “Initialize code review swarm with gh CLI” source section. - 03
Post initial review status
gh pr comment 123 --body "🔍 Multi-agent code review initiated" bash
gh pr comment 123 --body "🔍 Multi-agent code review initiated" bash - 04
2. Specialized Review Agents
Review the “2. Specialized Review Agents” section in the pinned source before continuing.
Review and apply the “2. Specialized Review Agents” source section. - 05
Security-focused review with gh CLI
Review the “Security-focused review with gh CLI” section in the pinned source before continuing.
Review and apply the “Security-focused review with gh CLI” source section.
Permission review
Static risk signals and limitations
Runs scripts
The documentation asks the agent to run terminal commands or scripts.
npx ruv-swarm github review-init \Runs scripts
The documentation asks the agent to run terminal commands or scripts.
npx ruv-swarm github review-performance \Evidence record
Why each signal appears
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 84/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 66,999 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- ruvnet/ruflo
- Skill path
- .agents/skills/agent-code-review-swarm/SKILL.md
- Commit
- 913f9eaedee92627950544424e50339feaf98271
- License
- MIT
- Collected
- 2026-08-04
- Default branch
- main
View the original 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 "$PR_DIFF" \
--agents "security,performance,style,architecture,accessibility" \
--depth comprehensive
# Post initial review status
gh pr comment 123 --body "🔍 Multi-agent code review initiated"
2. Specialized Review Agents
Security Agent
# Security-focused review with gh CLI
# Get changed files
CHANGED_FILES=$(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="$(gh pr view 123 --json headRefOid -q .headRefOid)"
done
Comment Templates
<!-- Security Issue Template -->
🔒 **Security Issue: [Type]**
**Severity**: 🔴 Critical / 🟡 High / 🟢 Low
**Description**:
[Clear explanation of the security issue]
**Impact**:
[Potential consequences if not addressed]
**Suggested Fix**:
```language
[Code example of the fix]
References:
### Batch Comment Management
```bash
# Manage review comments efficiently
npx ruv-swarm github review-comments \
--pr 123 \
--group-by "agent,severity" \
--summarize \
--resolve-outdated
Integration with CI/CD
Status Checks
# Required status checks
protection_rules:
required_status_checks:
contexts:
- "review-swarm$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
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