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

Adds substantial context beyond the annotations: pricing is per second of output, a plan is required, an account sign-in will be prompted by the host, and the call is typically asynchronous (>45 s, expect pending and poll get_job). The annotations only give the generic write/open-world/idempotency profile; the description supplies the operational reality.

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, zero filler, front-loaded with what is produced before the cost, latency, and auth consequences. Every clause carries information an agent needs before calling.

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 10-parameter paid, async, account-gated generation tool with an output schema, the description covers the missing pieces an agent must know: cost model, plan/account requirement, async polling expectation, and where to get valid model ids. Return values are rightly left to the output schema.

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 90%, so the schema already documents tier, model, prompt, aspect_ratio, duration, and even the conversation_id protocol. The description only confirms the prompt-or-start-image relationship and points at list_models for model ids; with the schema doing the heavy lifting, the baseline 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?

States a specific verb+resource ("Generate a short video") plus the inputs it accepts ("from a prompt and/or a start image") and the provider scope (StockCake's video models). This clearly separates it from the sibling generate_image, which is the nearest ambiguous alternative.

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?

Explicitly routes to list_models for model/tier selection and to get_job for polling, and states the prerequisites (paid plan, free StockCake account). It never says when NOT to use this tool (e.g. when the user wants a still image instead), so it stops short of a 5.

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