generate_image

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

No annotations are provided, so the description carries the full burden. It adds useful behavioral context: model versions with capabilities (e.g., 4.6 supports up to 4K), a default recommended model, and a caveat that negative_prompt is optional and may not be supported by all models. This goes beyond the schema, though it does not disclose rate limits, authentication, or async behavior.

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 one clear sentence followed by a concise bullet list of parameters. It is front-loaded with the purpose and avoids redundancy. Every line earns its place.

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?

For a 5-parameter tool with rich model options, the description covers all parameters with defaults and options, and an output schema exists to describe return values. It lacks guidance on when to choose specific models beyond the default recommendation, but overall it is sufficiently complete for an image generation tool.

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%, so the description fully compensates. It enumerates valid model values with human-readable meanings, aspect ratio options, quality levels, and explains negative_prompt semantics including a support caveat. This adds substantial meaning beyond the bare input schema.

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 '文生图：根据文字描述生成图片' (text-to-image: generate an image from a text description), using a specific verb and resource. It distinguishes itself from sibling tools like image_to_image and generate_video by explicitly framing itself as text-to-image.

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 implied through the 'text-to-image' framing: use this when you have a text description and want a generated image. However, there is no explicit when-not-to-use guidance or mention of alternative tools for related tasks (e.g., image_to_image for editing existing images).

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