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A task in an agent plan tells an agent what work to do, but it does not necessarily contain everything the agent can use—or determine what the agent is allowed to do. In OpenAI’s Agents SDK, the handoff input, conversation history, receiving agent’s instructions and tools, and application-side run context are distinct. Other agent frameworks may handle them differently.
What a task or handoff passes to the next agent
A handoff can pass the work request and, where configured, structured arguments. Those arguments may have a defined schema, and the handoff handler can receive their parsed values. The payload is therefore the task-specific input—not a catch-all for every setting or piece of runtime data.
See OpenAI’s Agents SDK handoffs guide for how handoff inputs and handlers work.
What else the receiving agent may receive
Conversation history
In the OpenAI Agents SDK, the handoffs guide says: “By default a handoff receives the entire conversation history.” That history is separate from the task’s handoff arguments. An input filter can alter what conversation history is passed along.
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Instructions
The receiving agent’s instructions define its role and how it should behave. They belong to its configuration; they are not automatically the same thing as the task payload. OpenAI’s agent definitions guide describes instructions as one part of an agent’s setup.
Tools
Tools are capabilities exposed to the agent. Their availability means the agent can call them; it does not mean the task has already called a tool or that every tool will be used.
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What stays in application-side run context
An application can create run context and make it available to tools, callbacks, and other runtime components. The OpenAI documentation distinguishes this application-side data from information sent to the model. Context may inform what runtime code does without becoming part of the model’s input.
The Agents SDK handoffs guide and Context Management guide explain context use across handoffs and other SDK components.
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Does a task plan grant permissions?
Do not assume that it does. A task description, an enabled tool, and an authorization rule are different things. The OpenAI pages cited here explain agent configuration, handoffs, and context; they do not establish a general rule that a plan grants permissions. Check the relevant application or runtime documentation to learn how access, approvals, and restrictions are actually enforced.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to check what a task receives in another framework
Do not treat the OpenAI Agents SDK behavior as universal. For a different framework or implementation, verify each input and capability separately:
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- Task payload: What text or structured arguments are passed, and are fields checked against a schema?
- Conversation history: Is prior history included, omitted, or filtered?
- Instructions: Which instructions are configured on the receiving agent?
- Tools: Which capabilities are exposed for that run?
- Runtime context: What application-side data can tools and callbacks access without being sent to the model?
- Authorization: Where are permissions and approval requirements defined and enforced?
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