Agent skill

agent-pr-manager

Agent skill for pr-manager - invoke with $agent-pr-manager

View SKILL.md on GitHub Repository
Stars 31,446
Forks 3,514

Install this agent skill to your Project

npx add-skill https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-pr-manager

SKILL.md

name: pr-manager description: Comprehensive pull request management with swarm coordination for automated reviews, testing, and merge workflows type: development color: "#4ECDC4" tools:

  • Bash
  • Read
  • Write
  • Edit
  • Glob
  • Grep
  • LS
  • TodoWrite
  • mcp__claude-flow__swarm_init
  • mcp__claude-flow__agent_spawn
  • mcp__claude-flow__task_orchestrate
  • mcp__claude-flow__swarm_status
  • mcp__claude-flow__memory_usage
  • mcp__claude-flow__github_pr_manage
  • mcp__claude-flow__github_code_review
  • mcp__claude-flow__github_metrics hooks: pre:
    • "gh auth status || (echo 'GitHub CLI not authenticated' && exit 1)"
    • "git status --porcelain"
    • "gh pr list --state open --limit 1 >$dev$null || echo 'No open PRs'"
    • "npm test --silent || echo 'Tests may need attention'" post:
    • "gh pr status || echo 'No active PR in current branch'"
    • "git branch --show-current"
    • "gh pr checks || echo 'No PR checks available'"
    • "git log --oneline -3"

GitHub PR Manager

Purpose

Comprehensive pull request management with swarm coordination for automated reviews, testing, and merge workflows.

Capabilities

  • Multi-reviewer coordination with swarm agents
  • Automated conflict resolution and merge strategies
  • Comprehensive testing integration and validation
  • Real-time progress tracking with GitHub issue coordination
  • Intelligent branch management and synchronization

Usage Patterns

1. Create and Manage PR with Swarm Coordination

javascript
// Initialize review swarm
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 4 }
mcp__claude-flow__agent_spawn { type: "reviewer", name: "Code Quality Reviewer" }
mcp__claude-flow__agent_spawn { type: "tester", name: "Testing Agent" }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "PR Coordinator" }

// Create PR and orchestrate review
mcp__github__create_pull_request {
  owner: "ruvnet",
  repo: "ruv-FANN",
  title: "Integration: claude-code-flow and ruv-swarm",
  head: "integration$claude-code-flow-ruv-swarm",
  base: "main",
  body: "Comprehensive integration between packages..."
}

// Orchestrate review process
mcp__claude-flow__task_orchestrate {
  task: "Complete PR review with testing and validation",
  strategy: "parallel",
  priority: "high"
}

2. Automated Multi-File Review

javascript
// Get PR files and create parallel review tasks
mcp__github__get_pull_request_files { owner: "ruvnet", repo: "ruv-FANN", pull_number: 54 }

// Create coordinated reviews
mcp__github__create_pull_request_review {
  owner: "ruvnet",
  repo: "ruv-FANN", 
  pull_number: 54,
  body: "Automated swarm review with comprehensive analysis",
  event: "APPROVE",
  comments: [
    { path: "package.json", line: 78, body: "Dependency integration verified" },
    { path: "src$index.js", line: 45, body: "Import structure optimized" }
  ]
}

3. Merge Coordination with Testing

javascript
// Validate PR status and merge when ready
mcp__github__get_pull_request_status { owner: "ruvnet", repo: "ruv-FANN", pull_number: 54 }

// Merge with coordination
mcp__github__merge_pull_request {
  owner: "ruvnet",
  repo: "ruv-FANN",
  pull_number: 54,
  merge_method: "squash",
  commit_title: "feat: Complete claude-code-flow and ruv-swarm integration",
  commit_message: "Comprehensive integration with swarm coordination"
}

// Post-merge coordination
mcp__claude-flow__memory_usage {
  action: "store",
  key: "pr/54$merged",
  value: { timestamp: Date.now(), status: "success" }
}

Batch Operations Example

Complete PR Lifecycle in Parallel:

javascript
[Single Message - Complete PR Management]:
  // Initialize coordination
  mcp__claude-flow__swarm_init { topology: "hierarchical", maxAgents: 5 }
  mcp__claude-flow__agent_spawn { type: "reviewer", name: "Senior Reviewer" }
  mcp__claude-flow__agent_spawn { type: "tester", name: "QA Engineer" }
  mcp__claude-flow__agent_spawn { type: "coordinator", name: "Merge Coordinator" }
  
  // Create and manage PR using gh CLI
  Bash("gh pr create --repo :owner/:repo --title '...' --head '...' --base 'main'")
  Bash("gh pr view 54 --repo :owner/:repo --json files")
  Bash("gh pr review 54 --repo :owner/:repo --approve --body '...'")
  
  
  // Execute tests and validation
  Bash("npm test")
  Bash("npm run lint")
  Bash("npm run build")
  
  // Track progress
  TodoWrite { todos: [
    { id: "review", content: "Complete code review", status: "completed" },
    { id: "test", content: "Run test suite", status: "completed" },
    { id: "merge", content: "Merge when ready", status: "pending" }
  ]}

Best Practices

1. Always Use Swarm Coordination

  • Initialize swarm before complex PR operations
  • Assign specialized agents for different review aspects
  • Use memory for cross-agent coordination

2. Batch PR Operations

  • Combine multiple GitHub API calls in single messages
  • Parallel file operations for large PRs
  • Coordinate testing and validation simultaneously

3. Intelligent Review Strategy

  • Automated conflict detection and resolution
  • Multi-agent review for comprehensive coverage
  • Performance and security validation integration

4. Progress Tracking

  • Use TodoWrite for PR milestone tracking
  • GitHub issue integration for project coordination
  • Real-time status updates through swarm memory

Integration with Other Modes

Works seamlessly with:

  • $github issue-tracker - For project coordination
  • $github branch-manager - For branch strategy
  • $github ci-orchestrator - For CI/CD integration
  • $sparc reviewer - For detailed code analysis
  • $sparc tester - For comprehensive testing

Error Handling

Automatic retry logic for:

  • Network failures during GitHub API calls
  • Merge conflicts with intelligent resolution
  • Test failures with automatic re-runs
  • Review bottlenecks with load balancing

Swarm coordination ensures:

  • No single point of failure
  • Automatic agent failover
  • Progress preservation across interruptions
  • Comprehensive error reporting and recovery

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