text_to_video

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

In the absence of annotations, the description discloses the async polling behavior and the return format (dict with keys). It does not mention potential side effects, but writes are not expected. It could add more on error handling or timeouts.

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 well-structured with sections for Args and Returns, but it is somewhat lengthy. Every sentence adds value, though some parameter details could be tighter. Still, it is appropriately 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?

Given the tool's complexity (13 parameters, async behavior, output schema), the description covers purpose, parameters, behavior, and return format adequately. It is complete enough for an agent to select and invoke the tool 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 0%, so the description bears full responsibility. It explains all 13 parameters with defaults, constraints (e.g., num_frames formula), precedence (image vs images), and common values, adding substantial meaning beyond the schema.

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 'Generate a video from text (and optional image(s))', which is a specific verb-resource pair. It also distinguishes from siblings like image_to_video and text_to_image by indicating the primary input modality.

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?

It notes that the operation is async and polls until completion, giving temporal expectations. It does not explicitly state when not to use this tool or name alternatives, but the context of siblings and the parameter descriptions imply usage scenarios.

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