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

Annotations only supply openWorldHint=true, so the description carries most of the burden. It usefully discloses that generation is asynchronous and yields a request ID rather than a video directly, which is the single most important behavioral fact here. It omits cost, latency, and rate-limit 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 first two sentences are near-duplicates ('Generate videos from text descriptions' vs 'Creates AI-generated videos based on your text prompt'), wasting a line. The return-value/next-step sentence is the only one carrying new information, so the text is not front-loaded efficiently.

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?

With 16 parameters, no output schema, and only a weak openWorld annotation, the description does cover the one thing the schema cannot: that the call returns a request ID to be polled via fetch-video. But it says nothing about model choice, defaults for the 14 optional params (fps, resolution, aspect_ratio), or generation constraints, leaving real gaps for a high-parameter 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 100% across all 16 parameters, so the schema already documents fps, resolution, aspect_ratio, negative_prompt, etc. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the work.

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+resource ('Generate videos from text descriptions') and confirms it creates AI-generated video from a prompt, which cleanly separates it from siblings like image-to-video and video-to-video. It never explicitly names those alternatives, but the resource is unambiguous.

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 implies the async workflow by noting the result is a request ID consumed by fetch-video, which is genuinely useful context. However, it gives no guidance on when to pick this tool over image-to-video or video-to-video, nor any prerequisites (e.g., model selection via list-models).

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