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Agent Orchestration
Command

/auto-agent

Automatically spawn and manage agents based on task requirements.

From plugin
ruflo
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Command definition

auto-agent.md

auto agent

Automatically spawn and manage agents based on task requirements.

Usage

npx claude-flow auto agent [options]

Options

  • `--task, -t <description>` - Task description for agent analysis
  • `--max-agents, -m <number>` - Maximum agents to spawn (default: auto)
  • `--min-agents <number>` - Minimum agents required (default: 1)
  • `--strategy, -s <type>` - Selection strategy: optimal, minimal, balanced
  • `--no-spawn` - Analyze only, don't spawn agents

Examples

Basic auto-spawning

npx claude-flow auto agent --task "Build a REST API with authentication"

Constrained spawning

npx claude-flow auto agent -t "Debug performance issue" --max-agents 3

Analysis only

npx claude-flow auto agent -t "Refactor codebase" --no-spawn

Minimal strategy

npx claude-flow auto agent -t "Fix bug in login" -s minimal

How It Works

1. **Task Analysis**

  • Parses task description
  • Identifies required skills
  • Estimates complexity
  • Determines parallelization opportunities

2. **Agent Selection**

  • Matches skills to agent types
  • Considers task dependencies
  • Optimizes for efficiency
  • Respects constraints

3. **Topology Selection**

  • Chooses optimal swarm structure
  • Configures communication patterns
  • Sets up coordination rules
  • Enables monitoring

4. **Automatic Spawning**

  • Creates selected agents
  • Assigns specific roles
  • Distributes subtasks
  • Initiates coordination

Agent Types Selected

  • **Architect**: System design, architecture decisions
  • **Coder**: Implementation, code generation
  • **Tester**: Test creation, quality assurance
  • **Analyst**: Performance, optimization
  • **Researcher**: Documentation, best practices
  • **Coordinator**: Task management, progress tracking

Strategies

Optimal

  • Maximum efficiency
  • May spawn more agents
  • Best for complex tasks
  • Highest resource usage

Minimal

  • Minimum viable agents
  • Conservative approach
  • Good for simple tasks
  • Lowest resource usage

Balanced

  • Middle ground
  • Adaptive to complexity
  • Default strategy
  • Good performance/resource ratio

Integration with Claude Code

// In Claude Code after auto-spawning
mcp__claude-flow__auto_agent {
  task: "Build authentication system",
  strategy: "balanced",
  maxAgents: 6
}

See Also

  • `agent spawn` - Manual agent creation
  • `swarm init` - Initialize swarm manually
  • `smart spawn` - Intelligent agent spawning
  • `workflow select` - Choose predefined workflows
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