delegation pattern

Delegation pattern enables main agents to assign subtasks to specialized sub-agents. **Mechanism**: Primary agent analyzes task, identifies subtasks requiring specialized skills, delegates to appropriate sub-agents, integrates results. **When to delegate**: Task requires specialized knowledge, subtask is well-defined, efficiency gain from specialization, reduces cognitive load on main agent. **Implementation**: Query router → specialist selection → context preparation → delegation call → result integration. **Specialist types**: Domain experts (legal, medical), tool specialists (code, web search), format experts (summarization, translation). **Context management**: Pass relevant context, not full conversation, minimize token usage, handle confidentiality. **Return protocols**: Structured results, confidence scores, error handling, partial results. **Delegation criteria**: Skill match, availability, cost/latency trade-offs. **Frameworks**: LangChain tool wrappers, CrewAI delegation, custom routing logic. **Best practices**: Clear task descriptions, verify delegation success, handle specialist failures, avoid infinite recursion. **Anti-patterns**: Over-delegation (everything needs specialist), under-delegation (monolithic agents). Effective delegation is key to scalable multi-agent architectures.