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

With no annotations, the description carries the full behavioral burden and falls short: it says nothing about whether this is a long-running/async job, cost or rate limits, audio behavior by default (generate_audio defaults true), or what the reference keys must point to. It only restates the capability.

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 waste. It is efficient, though efficient to the point of under-specification for a generative tool.

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 values need not be explained, but a generative tool with a nested object, 0% schema coverage and no annotations requires far more than one sentence about behavior, async semantics and optional inputs.

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% on a nested payload with six sub-properties. The description mentions the prompt, reference images and reference video but omits aspect_ratio, generate_audio, and reference_audio_key, and gives no format hints for the reference keys.

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?

States a specific verb (Generate) and resource (short video clip) with the driving input (a prompt). It implicitly separates itself from image-generation by naming video, but it does not explicitly name or differentiate against that sibling.

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?

No guidance on when to prefer this over image-generation or media-analysis, no prerequisites, no indication of typical runtime or async behavior. The agent is left to infer usage entirely from the tool name.

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