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

Annotations only mark this as a non-read-only, open-world call; the description adds the async nature ("Rendering takes minutes"), the return contract ("the answer carries the order id"), the human quality-review gate, and the x402 USDC payment terms with the Base-only deferred charge. These are precisely the facts an agent cannot infer from structured fields and would otherwise trip over.

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?

Three sentences, each load-bearing: what is produced, how to retrieve it, and what it costs. Output specs are front-loaded and the operational instructions follow in the order an agent needs them.

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 no output schema, the description still supplies the return value (order id) and the completion signal (get_order state done), which is the critical missing piece. Payment model and the review step round out everything needed to invoke and follow through correctly.

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 coverage is 100%, so both prompt and aspect are already documented in the input schema with an enum and a default. The description adds only the notion of a "text prompt" and no extra syntax or format guidance, so the schema baseline of 3 applies.

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 names a concrete verb and artifact with exact specs: "One 8 second video (2 shots, 480p, no audio) from a text prompt." The output shape and the reviewer step make it unmistakable against make_image, which produces a still image instead.

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?

It states the exact follow-up workflow — "poll get_order until the state is done" — so an agent knows this tool is the start of an async job rather than the whole flow. It does not explicitly say when to prefer this over make_image, so it falls short of full when/when-not routing.

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