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Orchestrate multi-agent swarms for complex parallel task execution
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Basé sur la classification professionnelle SOC
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| name | swarm-coordination |
| description | Orchestrate multi-agent swarms for complex parallel task execution |
| version | 1.0.0 |
| invocable | true |
| author | agentic-flow |
| capabilities | ["swarm_init","agent_spawn","task_orchestration","topology_optimization"] |
Coordinate multi-agent swarms for parallel task execution with intelligent topology selection.
# Initialize a mesh swarm with 5 agents
npx agentic-flow@alpha swarm init --topology mesh --agents 5
# Spawn specialized agents
npx agentic-flow@alpha swarm spawn --type researcher --name "Research Agent"
npx agentic-flow@alpha swarm spawn --type coder --name "Code Agent"
# Orchestrate a task
npx agentic-flow@alpha swarm orchestrate "Implement feature X with tests"
# Check swarm status
npx agentic-flow@alpha swarm status
| Type | Description | Use Case |
|---|---|---|
| researcher | Deep analysis | Requirements gathering |
| coder | Implementation | Feature development |
| tester | Quality assurance | Test creation |
| reviewer | Code quality | PR review |
| architect | System design | Architecture decisions |
| coordinator | Task routing | Complex workflows |
// Initialize swarm
mcp__claude-flow__swarm_init({ topology: "mesh", maxAgents: 8 })
// Spawn agent
mcp__claude-flow__agent_spawn({ type: "coder", name: "Feature Dev" })
// Orchestrate task
mcp__claude-flow__task_orchestrate({
task: "Implement OAuth",
strategy: "parallel"
})