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

No annotations are provided, so the description carries the full burden — and it delivers. It discloses the asynchronous 202-with-job-id behavior, the polling pattern via getApiJob with wait:30, the success-only credit charge capped at requested duration, the 50-job concurrency limit with the 429 PENDING_JOBS_LIMIT error, the HTTP 400 for incompatible model/duration, and request_id idempotency. This is exceptional behavioral disclosure for an unannotated tool.

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 long but every segment earns its place: differentiation, parameter semantics, async flow, rate limit, and pricing. The core purpose is front-loaded, and the operational details appear in logical order. Minor redundancy exists with pricing info already present in the model parameter's schema description, but consolidation into one billing summary is arguably beneficial.

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 an async job-submission tool with no output schema and no annotations, the description is complete: it names the result shape (video URL and actual duration), the polling endpoint and wait value, the error conditions, the rate limit, authentication scope, and the exact location of the final result (the result field matching this operation's documented response). Nothing an agent needs to call it correctly is missing.

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%, so the baseline is 3. The description adds meaningful cross-parameter context: the model/duration compatibility constraint and its 400 error, the credit-per-second rates per model, and the request_id's dual role for result lookup via GET /assets/videos/results — value beyond the individual parameter descriptions.

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 states a specific verb, resource, and scope: "Generate a video from 1-5 reference images and a text prompt (references-to-video)." It explicitly differentiates from the sibling createVideo by contrasting the input mode ("animates a single source image" vs "composes a new scene that borrows characters, objects, and style"), making tool selection 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 names its alternatives explicitly and the decision condition: "Unlike createVideo, which animates a single source image..." and "Related tools: createVideo for image-to-video, editVideo to modify a generated video." It also explains the async workflow (submit, poll getApiJob, read result), giving the agent a complete usage pathway without inference.

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