generate_video

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

With no annotations, the description provides useful behavioral context such as the approximate generation time (1–5 minutes) and model quality differences. However, it does not disclose asynchronous behavior, rate limits, or potential error conditions.

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 compact and front-loaded: a one-sentence purpose followed by a bulleted parameter list. Every line adds value without redundancy.

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 output schema exists and the tool's scope, the description covers key operational details: models, aspect ratios, duration, and time estimate. Minor omissions like prompt length limits or content restrictions leave small gaps.

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 no descriptions, but the description fully compensates by enumerating valid model options, aspect ratios, and duration choices (5 or 10 seconds). It adds significant meaning beyond the bare 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 the tool generates video from text (文生视频：根据文字描述生成视频), using a specific verb and resource. This distinguishes it from sibling tools like image_to_video and image_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?

The description makes it clear that this tool is for text-to-video generation, providing a clear context for when to use it. It does not explicitly exclude alternatives, but the input criterion (text description) is well-defined.

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