scaffolding-openai-agents

Multi-agent workflows with OpenAI Agents SDK use the Agent class to define individual agents and the Runner pattern to orchestrate handoffs and coordination between them. Define each agent with specific tools and instructions, then use Runner to manage execution flow, streaming responses, and state across agents in educational, development, and operational scenarios.

Function tools are reusable capabilities you register with agents to extend their functionality. Create them by defining functions that agents can call during execution, then register them with your Agent instance. This enables tool-calling agents to perform domain-specific tasks like API calls, data retrieval, or system operations within async/await patterns.

Yes, this Skill includes built-in guardrails for safety constraints and streaming response patterns. Configure guardrails at agent definition to enforce boundaries, and use streaming outputs to return responses incrementally. Both integrate with async/await patterns for production-ready agent deployments.

Agent handoffs transfer control from one agent to another using the Runner pattern and multi-agent orchestration. Define transition logic in your Runner configuration to route requests based on agent capabilities or task type, enabling agents to delegate work or escalate complex operations across your workflow.

Basic configurations define single agents with standard tools and settings. Advanced configurations add multi-agent orchestration, custom guardrails, structured outputs, model parameter tuning, and complex handoff logic. This Skill supports both through Agent class patterns and Runner verification checks for scaling from simple to production workflows.

Yes, structured outputs are supported for agents built with this Skill. Configure your Agent to enforce schema on responses, enabling downstream systems to parse and validate agent outputs reliably. Works with streaming responses and all orchestration patterns.