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midjourney_generate_video

Generate a video from a reference image with optional end frame and loop. Animate a still image using AI video generation.

Instructions

Generate a video from a reference image using Midjourney.

This creates an AI-generated video based on your description and a starting
frame image. Midjourney video generation is image-to-video only — a reference
image is always required. You can optionally specify an ending frame for more
control.

Use this when:
- You want to animate a still image
- You want to create short video clips from a reference image
- You need AI-generated video content

The generation process returns 4 video variations.

Returns:
    Task ID and video information including cover image and video URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_urlYesURL of the first-frame reference image when generating the video. Required for video generation (Midjourney video generation is image-to-video only and does not support pure text-to-video).
promptYesDescription of the video to generate. Examples: 'A cat walking on a table', 'Ocean waves crashing on the shore', 'Timelapse of clouds moving'
modeNoGeneration mode. 'fast' is recommended for most use cases.fast
resolutionNoVideo resolution. '720p' or '480p'.720p
end_image_urlNoOptional URL of the last frame reference image. Use this to control where the video ends.
loopNoIf true, generate a looping video where the end seamlessly connects to the beginning.
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
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that generation returns 4 video variations, requires a reference image, and optionally allows an end frame. It does not mention rate limits or auth, but covers key behavioral traits.

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

Conciseness4/5

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

The description is concise with bullet points for use cases and a clear returns section. It is well-structured without being verbose, though some redundancy exists with the returns section repeating output schema.

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 7 parameters and video generation complexity, the description covers purpose, required inputs, and output. It lacks details on error handling or processing time but is sufficient for an agent to decide when and how to use the tool.

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?

Schema coverage is 100%, so baseline is 3. The description adds context about image_url being required and generation constraints, but the schema already provides good descriptions. The additional value is limited.

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 that the tool generates a video from a reference image using Midjourney, specifying it is image-to-video only, which distinguishes it from potential text-to-video tools and from sibling tools like midjourney_extend_video.

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 explicit 'Use this when:' scenarios covering animation, short clips, and AI video generation. It contrasts with the image-to-video requirement but does not name specific alternatives for different use cases (e.g., text-to-video), though no such sibling exists.

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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