/auto-topology
Automatically select the optimal swarm topology based on task complexity analysis.
> /plugin marketplace add ruvnet/ruflo
Command definition
auto-topology.mdAutomatic Topology Selection
Purpose
Automatically select the optimal swarm topology based on task complexity analysis.
How It Works
1. Task Analysis
The system analyzes your task description to determine:
- Complexity level (simple/medium/complex)
- Required agent types
- Estimated duration
- Resource requirements
2. Topology Selection
Based on analysis, it selects:
- **Star**: For simple, centralized tasks
- **Mesh**: For medium complexity with flexibility needs
- **Hierarchical**: For complex tasks requiring structure
- **Ring**: For sequential processing workflows
3. Example Usage
**Simple Task:**
Tool: mcp__claude-flow__task_orchestrate
Parameters: {"task": "Fix typo in README.md"}
Result: Automatically uses star topology with single agent**Complex Task:**
Tool: mcp__claude-flow__task_orchestrate
Parameters: {"task": "Refactor authentication system with JWT, add tests, update documentation"}
Result: Automatically uses hierarchical topology with architect, coder, and tester agentsBenefits
- 🎯 Optimal performance for each task type
- 🤖 Automatic agent assignment
- ⚡ Reduced setup time
- 📊 Better resource utilization
Hook Configuration
The pre-task hook automatically handles topology selection:
{
"command": "npx claude-flow hook pre-task --optimize-topology"
}Direct Optimization
Tool: mcp__claude-flow__topology_optimize
Parameters: {"swarmId": "current"}CLI Usage
# Auto-optimize topology via CLI
npx claude-flow optimize topology
Read more
Automatic Topology Selection
Purpose
Automatically select the optimal swarm topology based on task complexity analysis.
How It Works
1. Task Analysis
The system analyzes your task description to determine:
- Complexity level (simple/medium/complex)
- Required agent types
- Estimated duration
- Resource requirements
2. Topology Selection
Based on analysis, it selects:
- **Star**: For simple, centralized tasks
- **Mesh**: For medium complexity with flexibility needs
- **Hierarchical**: For complex tasks requiring structure
- **Ring**: For sequential processing workflows
3. Example Usage
**Simple Task:**
Tool: mcp__claude-flow__task_orchestrate
Parameters: {"task": "Fix typo in README.md"}
Result: Automatically uses star topology with single agent**Complex Task:**
Tool: mcp__claude-flow__task_orchestrate
Parameters: {"task": "Refactor authentication system with JWT, add tests, update documentation"}
Result: Automatically uses hierarchical topology with architect, coder, and tester agentsBenefits
- 🎯 Optimal performance for each task type
- 🤖 Automatic agent assignment
- ⚡ Reduced setup time
- 📊 Better resource utilization
Hook Configuration
The pre-task hook automatically handles topology selection:
{
"command": "npx claude-flow hook pre-task --optimize-topology"
}Direct Optimization
Tool: mcp__claude-flow__topology_optimize
Parameters: {"swarmId": "current"}CLI Usage
# Auto-optimize topology via CLI npx claude-flow optimize topology
📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification. Agent = Model + Harness.
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