Multi-Agent Systems
Build coordinated multi-agent systems for complex tasks.
When to Use This Skill
Invoke this skill when:
- Tasks require multiple specialized agents
- Building orchestrator-worker patterns
- Implementing agent workflows
- Coordinating parallel execution
Parameter Schema
| Parameter | Type | Required | Description | Default |
|---|
task | string | Yes | Multi-agent goal | - |
architecture | enum | No | orchestrator-worker, hierarchical, peer-to-peer | orchestrator-worker |
framework | enum | No | langgraph, autogen, crewai | langgraph |
Quick Start
from langgraph.graph import StateGraph, MessagesState
from langgraph.prebuilt import create_react_agent
# Create specialized agents
researcher = create_react_agent(llm, [web_search])
coder = create_react_agent(llm, [execute_code])
# Build graph
graph = StateGraph(MessagesState)
graph.add_node("researcher", researcher)
graph.add_node("coder", coder)
graph.add_conditional_edges("coordinator", router)
Architecture Patterns
Orchestrator-Worker
Orchestrator (Opus)
├── Researcher (Sonnet)
├── Analyst (Sonnet)
└── Writer (Haiku)
Hierarchical
Manager (Opus)
├── Research Lead (Sonnet)
│ ├── Web Researcher (Haiku)
│ └── Doc Analyst (Haiku)
└── Engineering Lead (Sonnet)
├── Frontend Dev (Haiku)
└── Backend Dev (Haiku)
Model Allocation
| Agent Type | Model | Rationale |
|---|
| Orchestrator | Opus | Complex planning |
| Specialist | Sonnet | Reasoning |
| Worker | Haiku | Simple tasks |
Troubleshooting
| Issue | Solution |
|---|
| Agents not coordinating | Check message bus |
| Deadlock | Add timeout, detect cycles |
| Inconsistent results | Synchronize state |
| High costs | Use cheaper models for workers |
Best Practices
- One job per agent (single responsibility)
- Orchestrator handles planning only
- Use checkpointing for long workflows
- Implement circuit breakers per agent
Related Skills
ai-agent-basics - Single agentsagent-memory - Shared statetool-calling - Per-agent tools
References
