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sora_generate_video_with_character

Generate a new AI video featuring an animated character extracted from a reference video. Place the character in a scene described by your prompt.

Instructions

Generate an AI video featuring a character from a reference video.

This allows you to create new videos featuring a specific character
extracted from another video. The character will be placed in the
new scene described by the prompt.

IMPORTANT: The reference video must NOT contain real people.
Only animated or digital characters are supported.

Use this when:
- You want to reuse a character in different scenes
- You're creating a series with the same character
- You want consistent character appearance across videos

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate featuring the character. Describe the scene and action.
character_urlYesURL of the video containing the character to use. IMPORTANT: The video must NOT contain real people, only animated/digital characters.
character_startNoStart position of the character in the reference video (0-1 range). For example, 0.2 means the character appears at 20% from the start.
character_endNoEnd position of the character in the reference video (0-1 range). For example, 0.8 means the character ends at 80% of the video.
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 provided, so description carries full burden. It discloses the return includes Task ID and video info, and the limitation about real people. But it doesn't detail behavior like character selection from multi-character videos or potential mutation of the reference.

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?

Description is short and front-loaded with key purpose, followed by an important constraint and usage guidance. It is efficient but could be slightly more compact.

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

Completeness3/5

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

Given the presence of an output schema and high schema coverage, the description covers essential context. However, it lacks guidance on parameter choices (model, size, orientation) and does not fully address potential edge cases.

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 parameters are already well-documented. The description adds no new parameter semantics beyond the schema; it only weakly contextualizes prompt and character_url.

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 it generates AI videos featuring a character from a reference video, distinguishing it from sibling tools like sora_generate_video. It specifies the resource (video with character) and strongly implies the extraction process.

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' bullet points provide clear scenarios (reusing characters, creating series, consistent appearance). However, it lacks explicit mention of when NOT to use it versus alternatives like sora_generate_video.

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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