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veo_image_to_video

Convert images into AI-generated videos by animating between reference frames. Use one image to start a video, or multiple images to create transitions, with motion controlled by text prompts.

Instructions

Generate AI video from one or more reference images using Veo.

This creates a video using your image(s) as reference frames. The video
will animate from/between your provided images according to the prompt.

Image modes:
- 1 image: First-frame mode - the video starts from your image
- 2-3 images: First-last frame mode - video interpolates between images
- veo31-fast-ingredients model: Multi-image fusion - blends elements from all images

Use this when:
- You have a specific image you want to animate
- You want consistent visual style from a reference
- You need to create a video transition between two images

For video generation from text only, use veo_text_to_video instead.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video motion and action. Describe what should happen to the subject in the image. Examples: 'The coffee steam rises gently', 'The person turns and smiles at the camera', 'Camera slowly zooms out revealing the landscape'
image_urlsYesList of image URLs to use as reference. For first-frame mode, provide 1 image. For first-last frame mode, provide 2-3 images. The first image is the starting frame, the last image is the ending frame. Maximum 3 images.
modelNoVeo model version. Note: 'veo31-fast-ingredients' is for multi-image fusion mode only. Other models support 1 image (first frame) or 2-3 images (first/last frame).veo2
aspect_ratioNoVideo aspect ratio. Should typically match your input image aspect ratio for best results.16:9
translationNoIf true, automatically translate the prompt to English for better generation quality.
resolutionNoVideo resolution. Options: '4k' for highest quality, '1080p' for standard HD, 'gif' for animated GIF format.
callback_urlNoOptional URL to receive a POST callback when generation completes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by explaining the three image modes (1 image, 2-3 images, multi-image fusion), the animation behavior, and what the tool returns (task ID, video information including URLs and state). It doesn't mention rate limits, authentication needs, or cost implications, but provides substantial operational context.

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 efficiently structured with clear sections: purpose statement, image mode explanations, usage guidelines, and return information. Every sentence adds value, with no redundant information. The bullet-point format for image modes enhances readability without wasting space.

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

Completeness5/5

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

Given the tool's complexity (7 parameters, multiple operational modes), the description provides comprehensive context: explains the three image modes, when to use the tool, what it returns, and the alternative tool. With an output schema present, it doesn't need to detail return values, and the description adequately complements the well-documented schema.

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 description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds some value by explaining the image modes that relate to the image_urls parameter, but doesn't provide additional parameter semantics beyond what's in the schema. This meets the baseline for high schema coverage.

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 specific action ('Generate AI video from one or more reference images') and resource ('using Veo'), with explicit differentiation from sibling veo_text_to_video. It goes beyond the tool name by explaining the core functionality of animating from reference images.

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 'Use this when' scenarios (animating specific images, maintaining visual style, creating transitions) and clearly names the alternative tool ('veo_text_to_video') for text-only generation. This gives clear guidance on when to choose this tool versus its sibling.

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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