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wan_generate_video

Generate AI videos from text prompts. Describe the scene, motion, style, and mood to create custom videos with adjustable duration, resolution, and audio options.

Instructions

Generate AI video from a text prompt using Wan text-to-video model.

This uses the wan2.6-t2v model to create video from text descriptions.
For creating video from images, use wan_generate_video_from_image instead.

Returns:
    Task ID and generated video information including URLs and state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate. Be descriptive about the scene, motion, style, and mood.
negative_promptNoContent to exclude from the video. Maximum 500 characters.
durationNoVideo duration in seconds. Options: 5, 10, or 15. Default depends on model.
resolutionNoVideo resolution. Options: '480P', '720P' (default), '1080P'.720P
audioNoWhether the generated video should include audio. Default is false.
audio_urlNoURL of reference audio to use in the video. Only used when audio is enabled.
prompt_extendNoEnable LLM-based prompt rewriting for better results. Default is false.
sizeNoThe size of the generated video (e.g., '1280x720').
timeoutNoTimeout in seconds for the API to return data. Default is 1800.
callback_urlNoWebhook callback URL for asynchronous notifications. When provided, the API will call this URL when the video is generated.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries full transparency burden. It does not disclose whether the operation is async, how to handle callbacks, or any side effects. Key behavioral traits like task polling or timeout implications are omitted, leaving agents underinformed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences plus a returns statement, with no wasted words. It front-loads the core purpose and provides a clear differentiation, earning its brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers return values (Task ID, URLs, state) and mentions the model. However, it lacks details on async workflow, result retrieval (sibling tools exist but not referenced), and does not explain the callback mechanism. It is adequate but could be more complete given the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 10 parameters have schema descriptions (100% coverage). The description adds no extra meaning to parameters, only restating the prompt usage. Baseline 3 is appropriate as schema descriptions suffice, and the description does not enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function ('Generate AI video from a text prompt') and specifies the model (wan2.6-t2v). It explicitly differentiates from the sibling tool wan_generate_video_from_image, leaving no ambiguity about scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool (text prompts) and directs users to the alternative (wan_generate_video_from_image) for image inputs. This clear delineation helps agents select the correct tool.

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

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