gen_background

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

No annotations are provided, so the description carries the behavioral disclosure burden. It usefully notes that the tool is online and requires login, and the verb '生成' indicates it creates new assets rather than modifying existing ones. However, it does not describe output behavior, potential waiting times, video-vs-image behavioral differences, or failure modes, leaving significant behavioral gaps.

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 a single compact sentence that front-loads the action, names the platform, enumerates the output types, and adds the operational constraint '在线，需登录'. There is no filler; every segment contributes to a quick understanding of the tool.

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 10 parameters, zero required parameters, no output schema, and no annotations, the description carries a heavy burden to explain the overall invocation model, return values, and default behavior. It only gives a high-level capability statement and a login requirement, leaving ambiguity about what happens after generation, how video generation is triggered or awaited, and which parameter combinations are valid. The schema is rich, but the surrounding operational context is too thin.

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. The description itself adds little parameter-level meaning; it merely hints at video and general-image outputs that relate to 'video' and 'prompt'/'skill'. Since the schema already documents all parameters thoroughly, the description does not need to compensate here.

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 verb '生成' (generate) and the resources: wallpaper backgrounds, general images, or videos via the MUSE AV platform. This distinguishes it from the sibling tools (remove_bg, upscale_image, remove_watermark, compress_image), which are all post-processing operations rather than generation.

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 usage is implied: use this tool when generating wallpaper, general images, or video. However, it does not explicitly state when to use this tool versus the sibling alternatives, nor does it give exclusion conditions or guidance on choosing among skill/template/prompt modes. Some guidance exists in the schema, but the description itself stops at implication.

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