openai_create_response

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

No annotations are supplied, so the description carries the full behavioral burden and largely drops it. It says nothing about what 'store' means for persistence, whether calls are billable/rate-limited, what 'include_raw' returns, or what the sentinel defaults (-1 temperature, 0 max_output_tokens, empty strings) do.

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

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

A single front-loaded sentence with no filler — well structured for scanning. Its brevity is also its weakness, since the space saved is space the agent needed for the 14 opaque parameters.

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

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

An output schema exists, so return-value explanation is not required. But for a 14-parameter, unannotated API wrapper with zero schema coverage, one capability sentence leaves the agent without the payload-format and behavioral context needed to invoke it correctly.

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

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

Schema description coverage is 0% across 14 parameters, so the description must compensate and does not. Terms like 'tools', 'structured output', and 'image input' loosely gesture at tools_json/text_format_json/input_json, but there is no guidance on the JSON payload formats, the input_json-vs-input_text precedence, or the meaning of the negative/zero defaults.

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

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

The description gives a specific verb ('Call') and resource ('the Responses API') plus the capability surface (text, reasoning, image input, tools, structured output). It is clear what the tool does, but it never names or contrasts with the closest sibling, openai_create_chat_completion, so the agent must infer that this is the newer/alternate completion path.

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

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

Usage is only implied through the capability list; there is no explicit statement of when to choose this over openai_create_chat_completion or openai_safe_api_request. With 17 sibling tools, a routing sentence would materially help, but the capability enumeration does hint at the appropriate cases.

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