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Create response (OpenAI Responses API)

create_response

Creates a response using the OpenAI Responses API format. Supports models, input, tools, instructions, and streaming options.

Instructions

Create response (OpenAI Responses API) Creates a response using the native OpenAI Responses API shape. The model details must advertise the Responses request format and a same-protocol route must be currently available; model names and providers do not imply availability. Unknown request fields are forwarded on a best-effort basis and remain subject to the selected provider's support.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoText formatting options.
inputNoInput content as a string or structured item array.
modelYesModel to use
storeNoWhether the response is stored for later retrieval.
toolsNoTools available to the model. Tool types and combinations are validated by the selected service.
top_pNoNucleus sampling probability.
promptNoReference to a reusable prompt template and variables.
includeNoAdditional response sections to include when supported.
metadataNoRequest metadata.
reasoningNoReasoning configuration.
backgroundNoWhether to run the response asynchronously.
truncationNoTruncation strategy for long conversations.
temperatureNo
tool_choiceNoTool choice policy or explicit tool selection.
instructionsNoSystem instructions
service_tierNoService tier hint for compatible providers.
stream_optionsNoResponses streaming options.
max_output_tokensNoMaximum output tokens
parallel_tool_callsNoWhether the model may issue parallel tool calls.
previous_response_idNoID of a previous response to continue.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate non-read-only, open-world, non-idempotent, non-destructive. Description adds context about unknown field forwarding and model availability, but no additional behavioral traits like cost or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two dense sentences with redundant title repetition. Information is valuable but could be more structured and concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given high schema coverage and annotations, description covers key behavioral aspects. Lacks overview of typical use cases vs. siblings, but sufficient for tool understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 95%, so baseline 3 applies. Description does not add parameter-level information beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it creates a response using the OpenAI Responses API, distinguishing it from siblings like create_chat_completion by specifying the required model advertisement and route availability.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear conditions for use (model must advertise Responses format, same-protocol route available) and describes best-effort forwarding of unknown fields, but does not explicitly state when not to use or name alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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