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

With zero annotations, the description carries the full burden and delivers rich behavioral disclosure: the call returns immediately (async), returns a request_id and credit cost, requires polling at a specified cadence, has stated time expectations (1–5 min typical, up to 30 min), and failures are refunded. This is exactly the context an agent needs beyond the schema.

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?

Two sentences, front-loaded with the core action, followed by the critical async behavior and polling instruction. Every clause earns its place; nothing is redundant or wasted. The timing and refund details are packed into the second sentence without bloat.

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 a 7-parameter async tool with no output schema and no annotations, the description covers the key gaps an agent cannot infer: the return shape (request_id + cost), the follow-up procedure (polling target and cadence), expected latency, and failure handling. All parameters are fully documented in the schema, so nothing essential 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 baseline 3 applies. The description adds minimal parameter-level meaning beyond the schema — it echoes that prompt is the input text and image_url is optional ("optionally with a start image") — but the schema already documents all seven parameters, so the description does not need to compensate.

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 and resource — "Start a video generation from a text prompt" — and distinguishes itself from siblings: it explicitly names get_generation_status as the follow-up polling tool, and the phrase "optionally with a start image" adds the image-to-video scope. The word "Start" precisely signals asynchronous initiation rather than blocking generation.

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 gives clear workflow guidance: "Returns immediately... poll get_generation_status every 30 seconds until it completes," including expected duration bounds. However, it does not explicitly state when NOT to use this tool versus its siblings generate_image or list_models — the alternative selection is implied rather than stated.

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