Development
Command
/development
Coordinated development through specialized agent teams.
Install
$ npx -y skills add ruvnet/agentic-flow --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/development
Context preview
What this command does when you run it.
Coordinated development through specialized agent teams.
Command definition
development.mdDevelopment Swarm Strategy
Purpose
Coordinated development through specialized agent teams.
Activation
Using MCP Tools
// Initialize development swarm
mcp__claude-flow__swarm_init({
"topology": "hierarchical",
"maxAgents": 8,
"strategy": "balanced"
})
// Orchestrate development task
mcp__claude-flow__task_orchestrate({
"task": "build feature X",
"strategy": "parallel",
"priority": "high"
})Using CLI (Fallback)
`npx claude-flow swarm "build feature X" --strategy development`
Agent Roles
Agent Spawning with MCP
// Spawn development agents
mcp__claude-flow__agent_spawn({
"type": "architect",
"name": "System Designer",
"capabilities": ["system-design", "api-design"]
})
mcp__claude-flow__agent_spawn({
"type": "coder",
"name": "Frontend Developer",
"capabilities": ["react", "typescript", "ui"]
})
mcp__claude-flow__agent_spawn({
"type": "coder",
"name": "Backend Developer",
"capabilities": ["nodejs", "api", "database"]
})
mcp__claude-flow__agent_spawn({
"type": "specialist",
"name": "Database Expert",
"capabilities": ["sql", "nosql", "optimization"]
})
mcp__claude-flow__agent_spawn({
"type": "tester",
"name": "Integration Tester",
"capabilities": ["integration", "e2e", "api-testing"]
})Best Practices
- Use hierarchical mode for large projects
- Enable parallel execution
- Implement continuous testing
- Monitor swarm health regularly
Status Monitoring
// Check swarm status
mcp__claude-flow__swarm_status({
"swarmId": "development-swarm"
})
// Monitor agent performance
mcp__claude-flow__agent_metrics({
"agentId": "architect-001"
})
// Real-time monitoring
mcp__claude-flow__swarm_monitor({
"swarmId": "development-swarm",
"interval": 5000
})Error Handling
// Enable fault tolerance
mcp__claude-flow__daa_fault_tolerance({
"agentId": "all",
"strategy": "auto-recovery"
})Read more
Development Swarm Strategy
Purpose
Coordinated development through specialized agent teams.
Activation
Using MCP Tools
// Initialize development swarm
mcp__claude-flow__swarm_init({
"topology": "hierarchical",
"maxAgents": 8,
"strategy": "balanced"
})
// Orchestrate development task
mcp__claude-flow__task_orchestrate({
"task": "build feature X",
"strategy": "parallel",
"priority": "high"
})Using CLI (Fallback)
`npx claude-flow swarm "build feature X" --strategy development`
Agent Roles
Agent Spawning with MCP
// Spawn development agents
mcp__claude-flow__agent_spawn({
"type": "architect",
"name": "System Designer",
"capabilities": ["system-design", "api-design"]
})
mcp__claude-flow__agent_spawn({
"type": "coder",
"name": "Frontend Developer",
"capabilities": ["react", "typescript", "ui"]
})
mcp__claude-flow__agent_spawn({
"type": "coder",
"name": "Backend Developer",
"capabilities": ["nodejs", "api", "database"]
})
mcp__claude-flow__agent_spawn({
"type": "specialist",
"name": "Database Expert",
"capabilities": ["sql", "nosql", "optimization"]
})
mcp__claude-flow__agent_spawn({
"type": "tester",
"name": "Integration Tester",
"capabilities": ["integration", "e2e", "api-testing"]
})Best Practices
- Use hierarchical mode for large projects
- Enable parallel execution
- Implement continuous testing
- Monitor swarm health regularly
Status Monitoring
// Check swarm status
mcp__claude-flow__swarm_status({
"swarmId": "development-swarm"
})
// Monitor agent performance
mcp__claude-flow__agent_metrics({
"agentId": "architect-001"
})
// Real-time monitoring
mcp__claude-flow__swarm_monitor({
"swarmId": "development-swarm",
"interval": 5000
})Error Handling
// Enable fault tolerance
mcp__claude-flow__daa_fault_tolerance({
"agentId": "all",
"strategy": "auto-recovery"
}) Ships withagentic-flow
Production-ready AI agent orchestration with 66 self-learning agents, 213 MCP tools, and autonomous multi-agent swarms.
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Maintenance
TypeScript
Language
1d ago
Last commit
2y ago
Created
Repo: ruvnet/agentic-flow
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