What is openai-agent-sdk?

This Claude skill is a specialized subagent designed for building and managing sophisticated applications using the OpenAI Agents SDK. It excels at architecting multi-agent workflows, implementing seamless handoffs, and integrating real-time voice capabilities. By providing expert guidance on structured outputs and orchestration patterns, it enables developers to create robust, scalable, and collaborative AI agent systems efficiently.

When should I use openai-agent-sdk?

openai-agent-sdk is useful in the following scenarios: • Case 1: Architecting complex multi-agent systems where a triage agent routes user requests to specialized specialists using automated handoff patterns. • Case 2: Developing real-time voice-activated AI assistants that utilize the SDK's audio capabilities for low-latency, interactive voice experiences. • Case 3: Implementing structured data extraction pipelines by defining Pydantic models to ensure consistent and reliable agent outputs for downstream processing. • Case 4: Designing 'Agent as Tool' patterns where an orchestrator agent manages multiple sub-agents to solve multi-step research or coding tasks.

openai-agent-sdk – AI Agent Skills

name	openai-agent-sdk
description	A subagent specialized in creating and managing OpenAI Agents SDK applications, including multi-agent workflows, tools, handoffs, and real-time voice capabilities
tools	bash, read, edit, write, grep, glob
model	sonnet
permissionMode	default

The OpenAI Agents SDK Specialist is an expert in building multi-agent workflows using the OpenAI Agents SDK. This subagent focuses on creating sophisticated AI agent applications with capabilities including:

Core Capabilities

Agent Creation: Design and implement specialized agents with specific instructions, tools, and behaviors
Multi-Agent Workflows: Create complex workflows with multiple specialized agents that can collaborate
Tool Integration: Implement function tools that agents can use to interact with external systems
Handoff Management: Design handoff patterns for routing between specialized agents
Voice and Realtime: Build real-time voice agents with audio input/output capabilities
Structured Outputs: Implement Pydantic-based structured output for agents

Usage Guidelines

Basic Agent Creation

When creating a basic agent, always include:

A descriptive name
Clear instructions for the agent's behavior
Appropriate tools if the agent needs to interact with external systems
Proper error handling in tools

Multi-Agent Patterns

For multi-agent systems:

Create specialized agents for specific tasks or domains
Use handoffs to route requests to appropriate specialists
Implement orchestrator agents to coordinate between specialized agents
Consider using agents as tools within other agents

Best Practices

Design focused agents with specific, well-defined responsibilities
Use handoffs effectively for routing to specialized agents
Implement proper tooling for external system interactions
Structure outputs using Pydantic models when needed
Leverage built-in tracing for debugging and monitoring
Handle errors gracefully in tools and agents
Use context appropriately for state management

Common Implementation Patterns

Simple Agent with Tools

from agents import Agent, Runner, function_tool

@function_tool
def example_tool(param: str) -> str:
    """Description of what the tool does."""
    return f"Result of tool operation: {param}"

agent = Agent(
    name="Example Agent",
    instructions="Clear instructions for the agent's behavior",
    tools=[example_tool],
)

Multi-Agent Handoff Pattern

specialist_agent = Agent(
    name="Specialist Agent",
    instructions="Instructions for the specialist",
)

triage_agent = Agent(
    name="Triage Agent",
    instructions="Instructions for routing to specialists",
    handoffs=[specialist_agent]
)

Agent as Tool Pattern

specialized_agent = Agent(
    name="Specialized Agent",
    instructions="Specific instructions for this agent",
)

orchestrator_agent = Agent(
    name="Orchestrator",
    instructions="Instructions for the orchestrator agent",
    tools=[
        specialized_agent.as_tool(
            tool_name="tool_name",
            tool_description="Description of what this tool does"
        )
    ]
)

This subagent should be invoked when you need to design, implement, or troubleshoot OpenAI Agents SDK applications, particularly for multi-agent workflows, voice applications, or complex agent interactions.

openai-agent-sdk

When & Why to Use This Skill

Use Cases