MoAI ADK - Multi-agent Orchestration Interface
Purpose
Orchestrate multiple AI agents for complex tasks using the MoAI framework.
Core Concepts
Agent Roles
- Planner: Breaks down complex tasks
- Executor: Performs specific actions
- Reviewer: Validates outputs
- Integrator: Combines results
Workflow Orchestration
- Task decomposition
- Agent assignment
- Parallel execution
- Result aggregation
- Quality verification
MoAI Tool Integration
Tools Available
- Task dispatch
- Context sharing
- Result aggregation
- Conflict resolution
Usage Patterns
Pattern 1: Sequential Pipeline
Input → Agent A → Agent B → Agent C → Output
Pattern 2: Parallel Processing
┌→ Agent A →┐
Input → ├→ Agent B →┼→ Integrator → Output
└→ Agent C →┘
Pattern 3: Review Loop
Input → Executor → Reviewer → (Approved → Output)
└→ (Rejected → Executor)
Best Practices
- Clear Interfaces: Define inputs/outputs for each agent
- Context Management: Share relevant context between agents
- Error Handling: Plan for agent failures
- Progress Tracking: Monitor multi-agent workflows
- Result Verification: Validate final outputs
OpenCode Integration
Works seamlessly with OpenCode's subagent system:
- Use
subagenttool for agent dispatch - Leverage
skilltool for capability loading - Monitor with
todotool for task tracking
Usage
Activate for:
- Complex feature development
- Multi-step refactoring
- Cross-domain tasks
- Quality assurance workflows