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veo_image_to_video

Generate AI video from your reference images by animating a single image or creating smooth transitions between multiple images.

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, the description carries the full burden. It discloses the tool is generative, explains behavior based on image count and model selection, mentions auto-translation, and states return type (Task ID and info). However, it does not explicitly mention async nature or potential delays, though 'Task ID' implies it.

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 concise and well-structured: first paragraph states purpose, then image modes in a list, use cases, sibling tool reference, and return info. All sentences add value, and the most important info is front-loaded.

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 params, 2 enums, model-dependent behavior), the description is highly complete. It covers all scenarios, provides usage context, and explains return values sufficiently. The presence of an output schema reduces the need to detail return structure further.

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

Parameters5/5

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

Schema coverage is 100%, baseline 3. The description adds significant value beyond the schema: it explains image modes (1 vs 2-3 images), model restrictions (veo31-fast-ingredients only for multi-image fusion), aspect ratio best practices, translation purpose, and resolution options.

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 AI video from one or more reference images using Veo. It explains the primary function and distinguishes from veo_text_to_video by specifying that this tool uses images while the sibling is text-only.

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 explicitly lists use cases: 'Use this when: you have a specific image to animate, want consistent visual style, need video transition between two images.' It also provides an exclusion: 'For video generation from text only, use veo_text_to_video instead.'

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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