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

Annotations are mostly false hints, so they provide limited behavioral signal. The description adds valuable behavior not in annotations: the operation takes minutes and requires confirmation of rights to animate the content. It does not cover return format or polling, but it provides meaningful behavioral context.

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 short, front-loaded with the core function, and each sentence earns its place: what it does, expected duration, and required consent. No redundant or vague wording.

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 and a multi-minute operation, the description should explain what the agent will receive and how to follow up on the result. It does not mention returning a job ID, polling status via fattly_video_status, or any asynchronous callback pattern, leaving a meaningful gap for correct invocation.

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%, and all four parameters already have clear descriptions in the schema. The description adds no new parameter semantics beyond the brand label "Cinema Studio," so the baseline of 3 is appropriate.

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 concrete verb and resource: "brings a still photo to life as a video" and clarifies with "adds motion." This clearly distinguishes it from text-to-video siblings like fattly_generate_video, since this tool specifically animates an existing photo.

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 context on when to use the tool: when you have a still photo you want to turn into a video. It also sets timing expectations with "Takes a few minutes," though it does not explicitly name alternatives or state when not to use it.

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