create_response

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

With no annotations, the description discloses critical behaviors: statelessness, the need to send full history for multi-turn, the streaming behavior, and the debug-only nature of `include_raw_response`. It also clarifies server-side web-search tools. This rich behavioral context goes well beyond the bare minimum.

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?

The description is six sentences, each providing distinct value: purpose, input requirements, parameter usage, statelessness caveat, and debugging flag. It is front-loaded with the core purpose and avoids fluff. Highly efficient for the complexity covered.

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?

Given the tool's complexity (15 parameters, nested objects, no annotations, no output schema), the description covers the core operational aspects well, including state handling, streaming, and debugging. However, it omits a clear description of the default response format or return value, and since no output schema exists, this is a slight gap. Still, it is a strong contextual overview.

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?

The schema has 0% description coverage, so the description must compensate. It adds meaning for key parameters like `input`, `instructions`, `reasoning.effort`, `tools`, `stream`, and `include_raw_response`, but leaves many parameters (e.g., `text`, `user`, `model`, `top_p`, `temperature`, `tool_choice`, `max_output_tokens`) without any commentary. This is a partial compensation, not complete.

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 clearly states the tool creates a stateless DeepSeek V4 response via the Responses API, with a specific verb and resource. However, it does not explicitly distinguish itself from sibling tools like chat_completion or completion, so the differentiation is only implicit through 'Responses API' and 'stateless'.

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?

The description provides clear usage context: requiring `input`, `instructions`, or both; directing use of `reasoning.effort`, `tools`, `stream`, and `include_raw_response` for specific scenarios. It lacks explicit when-not-to-use guidance or alternative tool mentions, hence no full exclusionary guidance.

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