Customizing Agent Handoffs with Validation and Callbacks

Welcome back! In the previous lessons, you learned how to chain OpenAI agents together and delegate tasks using handoffs, allowing your multi-agent workflows to be both modular and intelligent. Today, you will take your agent coordination skills to the next level by learning how to customize handoffs. This means you will not only delegate tasks, but also control exactly how information is passed between agents, validate the data being transferred, and even run custom logic at the moment of handoff.

Why is this important? In real-world applications, you often need to ensure that the data passed between agents is correct and safe. You might also want to log certain events, trigger notifications, or preprocess information before the next agent takes over. By customizing handoffs, you make your agent workflows more robust, secure, and adaptable to complex scenarios.

By the end of this lesson, you will know how to:

• Enforce input validation and schemas when handing off tasks between agents,
• Use callbacks to run custom code during a handoff,
• Integrate these features into a real-world multi-agent workflow.

Let’s begin by briefly reminding ourselves how handoffs work and why we might want more control over them.

In the last lesson, you learned how to use the handoffs parameter to delegate tasks between agents. For example, you set up a triage agent that could route travel questions to a travel expert or safety concerns to a safety expert. The handoff process was automatic: the triage agent analyzed the request and passed it to the right specialist, along with the conversation history.

This approach works well for many cases, but sometimes you need more control. For example, what if you want to make sure the information passed to the safety expert always includes both a destination and a specific concern? Or what if you want to log every time a safety concern is escalated? This is where customizing handoffs becomes useful.

Let’s explore how you can achieve this using the handoff() function and its customization options.

The OpenAI Agents SDK provides a handoff() function that lets you fine-tune how handoffs work. Instead of just listing agents in the handoffs parameter, you can use handoff() to specify extra details and behaviors.

The main parameters you can customize are:

• agent: The agent to which you want to hand off the task.
• tool_name_override: Lets you set a custom name for the handoff action, making it clearer in logs or debugging.
• tool_description_override: Lets you provide a custom description for the handoff, which can help with documentation or agent prompting.
• input_type: Lets you specify a schema (using a Pydantic model) that the input must match before the handoff occurs.
• on_handoff: Lets you define a callback function that runs when the handoff is triggered. This is useful for logging, preprocessing, or any custom logic.

Let’s see how to use input validation and schema enforcement in practice.