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sora_generate_video_from_image

Generate AI videos from reference images by describing the desired motion. This tool animates static images into dynamic videos.

Instructions

Generate an AI video from reference images using Sora (Image-to-Video).

This allows you to animate or create videos based on provided images.
The AI will use the images as visual references for the generated video.

Use this when:
- You have reference images you want to animate
- You want the video to match a specific visual style
- You want to bring static images to life

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate based on the image. Describe the action or motion you want to see.
image_urlsYesList of reference image URLs to use for video generation. Can be image URLs or Base64 encoded images.
modelNoSora model version. 'sora-2' or 'sora-2-pro' for higher quality.sora-2
sizeNoVideo resolution. 'small' for lower resolution, 'large' for higher resolution.large
durationNoVideo duration in seconds. Options: 10, 15, or 25 (25 only for sora-2-pro).
orientationNoVideo orientation. 'landscape', 'portrait'.landscape

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions returns (task ID, video info) but does not disclose async behavior, wait times, or potential errors. The description is adequate but lacks depth for safety-critical aspects.

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 (10 sentences) with a clear front-loaded purpose, bulleted usage list, and returns section. Every sentence adds value, and the structure is easy to scan.

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 6 parameters, 100% schema coverage, and an output schema, the description effectively explains the tool's concept and usage. Missing some details like prerequisites (valid image URLs) or error handling, but overall sufficient.

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 baseline is 3. The description adds minimal extra meaning beyond schema descriptions (e.g., reiterates 'Describe action or motion'). No significant enhancement.

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 'Generate an AI video from reference images using Sora (Image-to-Video)', specifying both the verb and resource. It differentiates from sibling tools like sora_generate_video (no image) and sora_generate_video_with_character.

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 'Use this when:' list provides explicit scenarios (e.g., 'You have reference images you want to animate'). While it doesn't explicitly state when not to use, the context implies it's for image-to-video, differentiating from other tools.

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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