# Multi-Agent Architecture Patterns

## Core Architecture

### 1. Coordinator-Centric Pattern
```
┌─────────────────────────────────────────────────────┐
│                   User Request                      │
└──────────────────────────┬──────────────────────────┘
                           │
                    ┌──────▼──────┐
                    │  Coordinator │
                    │   Agent      │
                    └──────┬──────┘
                           │
      ┌──────────┬─────────┴─────────┬──────────┐
      │          │                   │          │
┌─────▼────┐ ┌──▼──────┐      ┌─────▼────┐ ┌──▼──────┐
│ Research │ │ Builder  │      │ Auditor  │ │Personal │
│  Agent   │ │  Agent   │      │  Agent   │ │ Assistant│
└──────────┘ └──────────┘      └──────────┘ └─────────┘
      │          │                   │          │
      └──────────┼───────────────────┼──────────┘
                 │                   │
          ┌──────▼───────────────────▼──────┐
          │       Shared Memory System      │
          └──────────────────────────────────┘
```

**When to use:** Most common pattern for business workflows where requests need intelligent routing.

**Key characteristics:**
- Single entry point (coordinator)
- Clear specialization boundaries
- Centralized routing logic
- Shared memory for coordination

### 2. Peer-to-Peer Pattern
```
┌──────────┐    ┌──────────┐    ┌──────────┐
│ Research │◄──►│  Builder │◄──►│  Auditor │
│  Agent   │    │  Agent   │    │  Agent   │
└──────────┘    └──────────┘    └──────────┘
      ▲              ▲              ▲
      │              │              │
┌─────┴──────────────┴──────────────┴─────┐
│            Event Bus System             │
└─────────────────────────────────────────┘
      │              │              │
┌─────▼──────────────▼──────────────▼─────┐
│              User Request               │
└─────────────────────────────────────────┘
```

**When to use:** Research-intensive or creative workflows where agents need to collaborate closely.

**Key characteristics:**
- No central coordinator
- Agents publish/subscribe to events
- Emergent coordination
- Higher complexity but more flexibility

### 3. Pipeline Pattern
```
┌──────────┐    ┌──────────┐    ┌──────────┐    ┌──────────┐
│ Research │───►│  Builder │───►│  Auditor │───►│  Deploy  │
│  Agent   │    │  Agent   │    │  Agent   │    │  Agent   │
└──────────┘    └──────────┘    └──────────┘    └──────────┘
```

**When to use:** Linear workflows like content creation, software development, or data processing pipelines.

**Key characteristics:**
- Sequential processing
- Each agent adds value to the workflow
- Clear handoff points
- Easy to monitor progress

## Agent Responsibilities

### Coordinator Agent
**Primary Role:** Request routing and system coordination

**Responsibilities:**
1. Analyze incoming requests to determine appropriate agent
2. Monitor agent availability and load
3. Handle request queuing and prioritization
4. Resolve conflicts between agent actions
5. Maintain system-wide consistency

**Configuration:**
```yaml
# SOUL.md excerpt
mission: "Route requests to appropriate specialist agents and ensure overall system coordination."
skills: ["routing", "load-balancing", "conflict-resolution"]
```

### Research Agent
**Primary Role:** Information gathering and synthesis

**Responsibilities:**
1. Perform targeted web searches
2. Extract key insights from research materials
3. Validate information from multiple sources
4. Present findings in actionable formats
5. Maintain research quality standards

**Configuration:**
```yaml
# SOUL.md excerpt
mission: "Gather, analyze, and synthesize information from web sources and databases."
skills: ["web-search", "data-analysis", "synthesis"]
tools: ["web_search", "web_fetch", "memory_search"]
```

### Builder Agent
**Primary Role:** Code and content creation

**Responsibilities:**
1. Write and review code in multiple languages
2. Implement file operations and system commands
3. Test functionality and debug issues
4. Document technical decisions
5. Follow coding standards and best practices

**Configuration:**
```yaml
# SOUL.md excerpt
mission: "Create, modify, and test code, scripts, and technical artifacts."
skills: ["coding", "debugging", "documentation"]
tools: ["exec", "write", "edit"]
```

### Auditor Agent
**Primary Role:** Quality assurance and compliance

**Responsibilities:**
1. Check code for security vulnerabilities
2. Validate data accuracy and consistency
3. Ensure compliance with operational guidelines
4. Provide constructive feedback for improvement
5. Maintain audit trails and reports

**Configuration:**
```yaml
# SOUL.md excerpt
mission: "Review outputs for quality, security, and compliance with standards."
skills: ["security-review", "quality-assurance", "compliance"]
tools: ["read", "exec", "memory_search"]
```

### Personal Assistant Agent
**Primary Role:** Scheduling and communication

**Responsibilities:**
1. Manage calendars and reminders
2. Handle email and message composition
3. Coordinate personal workflows
4. Provide timely notifications
5. Maintain communication logs

**Configuration:**
```yaml
# SOUL.md excerpt
mission: "Handle personal assistant tasks, scheduling, and communication."
skills: ["scheduling", "communication", "organization"]
tools: ["message", "cron", "tts"]
```

## Shared Memory Design

### Data Structure
```json
{
  "version": "1.0",
  "agents": {
    "coordinator": {
      "status": "active",
      "last_active": "2026-04-02T14:00:00Z",
      "workload": 0.3
    }
  },
  "shared": {
    "current_task": {
      "id": "task_123",
      "type": "research",
      "assigned_to": "research",
      "status": "in_progress"
    },
    "research_findings": {
      "topic": "ClawHub marketplace trends",
      "summary": "Multi-agent skills are in high demand",
      "sources": ["clawoneclick.com", "github.com"],
      "timestamp": "2026-04-02T14:05:00Z"
    }
  },
  "events": [
    {
      "type": "task_assigned",
      "agent": "coordinator",
      "data": {"task_id": "task_123", "to": "research"},
      "timestamp": "2026-04-02T14:00:00Z"
    }
  ]
}
```

### Synchronization Strategies

**1. Polling Strategy**
- Agents periodically check for updates
- Simple to implement
- Higher latency
- Higher resource usage

**2. Event-Driven Strategy**
- Agents subscribe to specific event types
- Low latency
- Complex to implement
- Requires event bus infrastructure

**3. Hybrid Strategy**
- Critical updates use events
- Non-critical updates use polling
- Balances complexity and performance

## Communication Protocols

### Inter-Agent Messages
```json
{
  "message_id": "msg_abc123",
  "sender": "research",
  "recipient": "coordinator",
  "type": "task_complete",
  "payload": {
    "task_id": "task_123",
    "result": "Research findings attached",
    "attachments": ["findings.md"]
  },
  "timestamp": "2026-04-02T14:10:00Z",
  "priority": "normal"
}
```

### Message Types
1. **Task Assignment** - Coordinator → Specialist
2. **Task Completion** - Specialist → Coordinator
3. **Information Request** - Any → Any
4. **Error Report** - Any → Coordinator
5. **Status Update** - Any → Shared Memory

### Priority Levels
- **Critical**: Immediate attention required (errors, failures)
- **High**: Time-sensitive tasks
- **Normal**: Routine communication
- **Low**: Background updates, logging

## Performance Optimization

### Load Balancing
```python
def assign_task(task, agents):
    """Assign task to least busy agent."""
    available_agents = [
        agent for agent in agents 
        if agent.status == "active" 
        and agent.workload < 0.8
    ]
    
    if not available_agents:
        return None
    
    # Choose agent with lowest workload
    return min(available_agents, key=lambda a: a.workload)
```

### Caching Strategies
1. **Agent-level cache**: Frequently accessed data per agent
2. **Shared cache**: Common data across all agents
3. **Result cache**: Store completed task results
4. **Configuration cache**: System settings and routing rules

### Monitoring Metrics
- **Response time**: Time from request to first response
- **Throughput**: Requests processed per minute
- **Error rate**: Percentage of failed requests
- **Agent utilization**: Percentage of time agents are busy
- **Memory usage**: Shared memory consumption
- **Queue length**: Pending tasks waiting for agents

## Security Considerations

### Isolation Boundaries
1. **Workspace isolation**: Each agent has separate workspace
2. **Memory isolation**: Agents can only access shared memory via API
3. **Tool restrictions**: Agents have only necessary tools
4. **Network isolation**: Agents cannot make arbitrary network calls

### Permission Model
```yaml
agent_permissions:
  coordinator:
    can_assign_tasks: true
    can_read_all_memory: true
    can_write_shared_memory: true
    
  research:
    can_assign_tasks: false
    can_read_shared_memory: true
    can_write_shared_memory: true
    can_access_web: true
    
  builder:
    can_assign_tasks: false
    can_read_shared_memory: true
    can_write_shared_memory: false
    can_exec_commands: true
```

### Audit Logging
- All inter-agent communication
- Shared memory write operations
- Tool usage (especially exec commands)
- Configuration changes
- Error conditions and resolutions

## Scaling Strategies

### Vertical Scaling
- Increase resources for individual agents
- Suitable for CPU/memory-intensive agents
- Limited by single machine capacity

### Horizontal Scaling
- Deploy multiple instances of the same agent type
- Use load balancer for distribution
- Requires state synchronization

### Hybrid Scaling
- Scale critical agents horizontally
- Scale non-critical agents vertically
- Use cloud auto-scaling where available

## Troubleshooting Common Issues

### Agent Unresponsiveness
1. Check agent process status
2. Verify workspace permissions
3. Check shared memory connectivity
4. Review recent error logs
5. Restart agent if necessary

### Memory Synchronization Issues
1. Verify shared memory directory permissions
2. Check for file locking conflicts
3. Validate JSON data structure
4. Review synchronization frequency
5. Test with simple read/write operations

### Routing Failures
1. Verify routing configuration syntax
2. Check agent availability
3. Review request matching patterns
4. Test fallback routing
5. Monitor coordinator agent logs

## Best Practices

### 1. Start Simple
Begin with 2-3 agents and expand as needed. Over-engineering early leads to complexity.

### 2. Define Clear Boundaries
Each agent should have unambiguous responsibilities. Avoid overlapping functionality.

### 3. Implement Gradual Degradation
When one agent fails, the system should continue functioning with reduced capabilities.

### 4. Monitor Early and Often
Implement monitoring from day one. Track both system metrics and business outcomes.

### 5. Regular Testing
Test agent coordination, error handling, and recovery procedures regularly.

### 6. Documentation Updates
Keep architecture documentation current as the system evolves.

### 7. Security First
Implement security controls early. Assume agents will make mistakes.

### 8. Plan for Evolution
Design for change. Agents will need updates, new agents will be added, requirements will shift.