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wan_generate_video

Create a video from a text prompt with Wan AI. Describe scene, motion, style, and mood to generate video with adjustable resolution, duration, and audio.

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only mentions the return type (task ID and video info) but does not disclose any side effects, authentication needs, rate limits, or resource implications. For a generation tool, this is insufficient.

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 extremely concise with three sentences, each adding value. It front-loads the purpose and model, then offers alternative direction, and finally states returns. No wasted words.

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

Completeness4/5

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

Given the tool's complexity (10 parameters, output schema exists), the description is fairly complete. It specifies the model, distinguishes alternative tools, and notes the output, which is sufficient when combined with the schema. Minor gap: no mention of typical usage patterns or prompt guidance, but the schema covers prompt description.

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?

The input schema has 100% coverage with descriptions for all 10 parameters. The description adds little beyond the schema, only referencing the prompt implicitly. Baseline 3 is appropriate as the schema already provides adequate meaning.

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 generates AI video from a text prompt using the Wan text-to-video model, specifically wan2.6-t2v. It distinguishes itself from the sibling tool wan_generate_video_from_image by explicitly noting the image-based alternative.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool (text-to-video generation) and directs users to the sibling tool for image-to-video. However, it does not mention when not to use it or any prerequisites, limiting full guidance.

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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