wan_text_to_video

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

No annotations are provided, so the description carries the burden. It usefully discloses that all non-prompt parameters have sensible defaults and that the model and text encoder are auto-detected. However, it omits details about output handling, error conditions, or resource implications (e.g., computation time, VRAM usage).

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 two sentences with no filler. The first sentence states the purpose and model, and the second communicates key behavioral shortcuts. It is well-structured and 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?

With 14 parameters, the description is compact, but the schema describes each parameter, and an output schema exists to cover return values. The description covers the most important behavioral aspects (defaults, auto-detection) and is sufficient for an agent to decide to use the tool. It could mention how to direct the output, but that is likely covered by 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 coverage is 100%, giving a baseline of 3. The description adds value by clarifying that all parameters except prompt are optional with sensible defaults and that diffusion_model and clip_name with empty strings are auto-detected, which explains the schema's default values and reduces uncertainty about model selection.

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 uses a specific verb ('Generate video') and identifies the exact resource ('Wan 2.2 (local model)'), which clearly differentiates it from sibling tools like text_to_image or wan_image_to_video. The phrase 'from text' makes the modality explicit.

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 suggests the use case (text-to-video with Wan 2.2) and adds 'local model' as context, but it does not explicitly contrast with alternatives such as text_to_video or wan_image_to_video. There is no when-not-to-use guidance or mention of sibling tools.

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