SKILL.md
Swarm Orchestration Skill
Purpose
Multi-agent swarm coordination for complex tasks. Uses hierarchical topology with specialized agents to break down and execute complex work across multiple files and modules.
When to Trigger
- 3+ files need changes
- new feature implementation
- cross-module refactoring
- API changes with tests
- security-related changes
- performance optimization across codebase
- database schema changes
When to Skip
- single file edits
- simple bug fixes (1-2 lines)
- documentation updates
- configuration changes
- quick exploration
Commands
Initialize Swarm
Start a new swarm with hierarchical topology (anti-drift)
npx @claude-flow/cli swarm init --topology hierarchical --max-agents 8 --strategy specialized
Example:
npx @claude-flow/cli swarm init --topology hierarchical --max-agents 6 --strategy specialized
Route Task
Route a task to the appropriate agents based on task type
npx @claude-flow/cli hooks route --task "[task description]"
Example:
npx @claude-flow/cli hooks route --task "implement OAuth2 authentication flow"
Spawn Agent
Spawn a specific agent type
npx @claude-flow/cli agent spawn --type [type] --name [name]
Example:
npx @claude-flow/cli agent spawn --type coder --name impl-auth
Monitor Status
Check the current swarm status
npx @claude-flow/cli swarm status --verbose
Orchestrate Task
Orchestrate a task across multiple agents
npx @claude-flow/cli task orchestrate --task "[task]" --strategy adaptive
Example:
npx @claude-flow/cli task orchestrate --task "refactor auth module" --strategy parallel --max-agents 4
List Agents
List all active agents
npx @claude-flow/cli agent list --filter active
Scripts
Script
Path
Description
swarm-start
.agents/scripts/swarm-start.sh
Initialize swarm with default settings
swarm-monitor
.agents/scripts/swarm-monitor.sh
Real-time swarm monitoring dashboard
References
Document
Path
Description
Agent Types
docs/agents.md
Complete list of agent types and capabilities
Topology Guide
docs/topology.md
Swarm topology configuration guide
Best Practices
- Check memory for existing patterns before starting
- Use hierarchical topology for coordination
- Store successful patterns after completion
- Document any new learnings