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Testing
Command

/swarm-init

Initialize a Claude Flow swarm with specified topology and configuration.

From plugin
agentic-qe
436149 skills169 agents149 commands
Install
> /plugin marketplace add proffesor-for-testing/agentic-qe
> /plugin install agentic-qe-fleet@agentic-qe

How 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/swarm-init

Context preview

What this command does when you run it.

Initialize a Claude Flow swarm with specified topology and configuration.

Command definition

swarm-init.md

swarm init

Initialize a Claude Flow swarm with specified topology and configuration.

Usage

npx claude-flow swarm init [options]

Options

  • `--topology, -t <type>` - Swarm topology: mesh, hierarchical, ring, star (default: hierarchical)
  • `--max-agents, -m <number>` - Maximum number of agents (default: 8)
  • `--strategy, -s <type>` - Execution strategy: balanced, parallel, sequential (default: parallel)
  • `--auto-spawn` - Automatically spawn agents based on task complexity
  • `--memory` - Enable cross-session memory persistence
  • `--github` - Enable GitHub integration features

Examples

Basic initialization

npx claude-flow swarm init

Mesh topology for research

npx claude-flow swarm init --topology mesh --max-agents 5 --strategy balanced

Hierarchical for development

npx claude-flow swarm init --topology hierarchical --max-agents 10 --strategy parallel --auto-spawn

GitHub-focused swarm

npx claude-flow swarm init --topology star --github --memory

Topologies

Mesh

  • All agents connect to all others
  • Best for: Research, exploration, brainstorming
  • Communication: High overhead, maximum information sharing

Hierarchical

  • Tree structure with clear command chain
  • Best for: Development, structured tasks, large projects
  • Communication: Efficient, clear responsibilities

Ring

  • Agents connect in a circle
  • Best for: Pipeline processing, sequential workflows
  • Communication: Low overhead, ordered processing

Star

  • Central coordinator with satellite agents
  • Best for: Simple tasks, centralized control
  • Communication: Minimal overhead, clear coordination

Integration with Claude Code

Once initialized, use MCP tools in Claude Code:

mcp__claude-flow__swarm_init { topology: "hierarchical", maxAgents: 8 }

See Also

  • `agent spawn` - Create swarm agents
  • `task orchestrate` - Coordinate task execution
  • `swarm status` - Check swarm state
  • `swarm monitor` - Real-time monitoring
Read more
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