text_to_video

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

With no annotations, the description carries the full burden of disclosing behavior. It mentions that the tool returns a task id, status, and output URLs, but omits critical aspects like the async task lifecycle, polling behavior, and the need to call get_task when wait=false. It also does not disclose potential side effects or the fact that reference_image_urls is ignored.

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 only two sentences, front-loaded with the main verb and purpose, and contains no filler words. Every word earns its place.

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 12-parameter async task tool with no annotations or output schema, the description is too sparse. It lacks essential context about the task lifecycle, the role of callback_url, and the meaning of safety checker settings, leaving the agent to rely heavily on the 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 83%, which is high, so the baseline is 3. The description adds no parameter-level details, but the mention of returning task id and output URLs loosely relates to the wait parameter.

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 clearly states the tool creates a Grok Imagine text-to-video task, using a specific verb and resource. The phrase 'text to video' distinguishes it from sibling tools like text_to_image and image_to_video.

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 explicitly identifies the tool's purpose as text-to-video generation, which provides clear context for when to use it. However, it does not mention exclusions or directly contrast it with alternative tools, though sibling names make the differentiation obvious.

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