wan_image_to_video

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

With no annotations, the description carries the full burden. It discloses local model execution, auto-detection of the Wan model/encoder, and default-driven parameter behavior. However, it omits other behavioral aspects such as output handling, resource requirements, or potential side effects, though the output schema may cover return values.

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 wasted words. It front-loads the primary purpose and then gives a concise, useful note about optionality and auto-detection. Every sentence contributes value.

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 15 parameters and a schema covering all parameter descriptions and defaults, the description is sufficiently complete. It covers the model variant, local execution, and auto-detection behavior. It does not explicitly discuss when to prefer this over generic image_to_video, but the tool name and sibling list provide reasonable context.

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?

Since the schema has 100% coverage with default values and descriptions, the baseline is 3. The description adds meaningful semantic context by explicitly stating that only prompt and input_image are required and that clip_name/diffusion_model auto-detect when left empty, going beyond what the schema individually states.

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+resource: 'Generate video from an image using Wan 2.2 (local model).' This clearly identifies what the tool does and distinguishes it from sibling tools like wan_text_to_video and generic image_to_video by specifying the input type and model variant.

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 states a clear use case ('from an image') and identifies the model (Wan 2.2 local). It also provides practical guidance about optional parameters and auto-detection. However, it does not explicitly name alternatives or exclusion conditions, so it stops short of full 5.

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