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

With no annotations provided, the description carries the full behavioral burden and does so thoroughly. It discloses that the call is asynchronous, that rendering takes two to four minutes, that credits are charged and automatically refunded on failure, and that the agent should tell the user rendering is in progress rather than going silent.

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 dense but every sentence earns its place: async behavior first, then polling guidance, billing, model options, and default behavior. Bulleted model details are scannable, and the most important operational warning—do not poll faster than 15 seconds—is front-loaded.

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 generation tool with seven parameters and no output schema, the description is unusually complete. It covers the response shape (job id), follow-up call, timing, billing, model selection, and parameter constraints, leaving an agent with everything needed to invoke and monitor the operation 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 description coverage is 100%, so the baseline is 3, but the description adds real value beyond the schema by explaining per-model capabilities, durations, resolutions, audio support, pricing differences, and the default model behavior. It also gives practical guidance like describing subject, action, camera move, and lighting, which goes beyond the schema's own wording.

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 opens with a specific verb and resource: 'Render a video from a text prompt using ViewMax Studio.' It also clearly distinguishes this tool from its sibling get_video by explaining that it returns a job id and that the clip is not ready yet, so an agent can immediately tell which tool to call first.

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 explicit follow-up instructions: call get_video with the returned id, wait about 15 seconds between checks, and do not poll faster. It also tells the agent when to use list_video_models for exact limits/prices and says to leave model unset for the default, leaving little ambiguity about workflow.

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