Orchestrating Multi Agent Systems

Prerequisites

Before using this skill, ensure you have:

• Node.js 18+ installed for TypeScript agent development
• AI SDK v5 package installed (npm install ai)
• API keys for AI providers (OpenAI, Anthropic, Google, etc.)
• Understanding of agent-based architecture patterns
• TypeScript knowledge for agent implementation
• Project directory structure for multi-agent systems

Instructions

Step 1: Initialize Project Structure

Set up the foundation for your multi-agent system:

1. Create project directory with necessary subdirectories
2. Initialize npm project with TypeScript configuration
3. Install AI SDK v5 and provider-specific packages
4. Set up configuration files for agent orchestration

Step 2: Define Agent Roles

Identify and specify specialized agents needed:

• Determine agent responsibilities and capabilities
• Define agent system prompts with clear instructions
• Specify tools each agent can access
• Establish agent communication protocols

Step 3: Implement Agents

Create individual agent files with proper configuration:

1. Write agent initialization code with AI SDK
2. Configure system prompts for agent behavior
3. Define tool functions for agent capabilities
4. Implement handoff rules for inter-agent delegation

Step 4: Configure Orchestration

Set up coordination between agents:

• Define workflow sequences for task processing
• Implement routing logic for task distribution
• Configure handoff mechanisms between agents
• Set up state management for multi-step workflows

Step 5: Test and Refine

Validate the multi-agent system functionality:

• Test individual agent responses and behaviors
• Verify handoff execution between agents
• Validate routing logic with different input scenarios
• Monitor coordination and identify bottlenecks

Output

The skill generates a complete multi-agent system including:

Project Structure

{baseDir}/
├── agents/
│   ├── coordinator.ts       # Main orchestration agent
│   ├── specialist-1.ts      # Domain-specific agent
│   ├── specialist-2.ts      # Domain-specific agent
│   └── [additional agents]
├── orchestration/
│   ├── workflow.ts          # Workflow definitions
│   ├── routing.ts           # Routing logic
│   └── handoffs.ts          # Handoff configurations
├── tools/
│   └── [agent tools]        # Shared tool implementations
├── config/
│   └── agents.config.ts     # Agent configurations
└── package.json             # Dependencies

Agent Implementation Files

• TypeScript files with AI SDK v5 integration
• System prompts tailored to each agent role
• Tool definitions and implementations
• Handoff rules and coordination logic

Orchestration Configuration

• Workflow definitions for task sequences
• Routing rules for intelligent task distribution
• State management for multi-step processes
• Error handling and fallback mechanisms

Documentation

• Agent role descriptions and capabilities
• Workflow diagrams showing agent interactions
• API documentation for agent endpoints
• Usage examples for common scenarios

Error Handling

Common issues and solutions:

Agent Initialization Failures

• Error: AI SDK provider configuration invalid
• Solution: Verify API keys in environment variables, check provider-specific setup requirements

Handoff Execution Errors

• Error: Agent handoff fails or creates circular dependencies
• Solution: Review handoff rules for clarity, implement handoff depth limits, add fallback agents

Routing Logic Failures

• Error: Tasks routed to incorrect agent or no agent
• Solution: Refine routing criteria, add default routing rules, implement topic classification improvement

Tool Access Violations

• Error: Agent attempts to use unauthorized tools
• Solution: Review tool permissions per agent, implement proper access control, validate tool configurations

Workflow Deadlocks

• Error: Multi-agent workflow stalls without completion
• Solution: Implement timeout mechanisms, add workflow monitoring, design escape conditions for stuck states

Resources

AI SDK Documentation

• AI SDK v5 official documentation for agent creation
• Provider-specific integration guides (OpenAI, Anthropic, Google)
• Tool definition and implementation examples
• Handoff and routing pattern references

Multi-Agent Architecture Patterns

• Coordinator-worker pattern for task distribution
• Pipeline pattern for sequential processing
• Hub-and-spoke pattern for centralized coordination
• Peer-to-peer pattern for collaborative agents

Agent Design Best Practices

• Single responsibility principle for agent specialization
• Clear handoff criteria and routing rules
• Comprehensive error handling and fallbacks
• State management for complex workflows
• Testing strategies for multi-agent systems

Example Use Cases

• Code generation pipelines with specialized agents
• Customer support routing systems
• Research and analysis workflows
• Content creation and review pipelines
• Data processing and validation systems