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create_video

Generate a video from a text prompt using Sora. Optionally add a reference image to guide style. Returns a video ID for tracking progress.

Instructions

Create a new Sora video generation job. This starts an async job and returns immediately with a video_id.

The video is NOT ready immediately - use get_video_status(video_id) to poll for completion. Status will be 'queued' -> 'in_progress' -> 'completed' or 'failed'. Once status='completed', use download_video(video_id) to save the video to disk.

Parameters:

  • prompt: Text description of the video to generate (required)

  • model: "sora-2" (faster, cheaper) or "sora-2-pro" (higher quality). Default: "sora-2"

  • seconds: Duration as string "4", "8", or "12" (NOT an integer). Default: varies by model

  • size: Resolution as "720x1280" (portrait), "1280x720" (landscape), "1024x1792", or "1792x1024". Default: "720x1280"

  • input_reference_filename: Filename of reference image in IMAGE_PATH (e.g., "cat.png"). Use list_reference_images to find available images. Image must match target size. Supported: JPEG, PNG, WEBP. Optional.

Returns Video object with fields: id, status, progress, model, seconds, size.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo
modelNosora-2
promptYes
secondsNo
input_reference_filenameNo
Behavior5/5

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

The description fully discloses the async nature, immediate return, status progression, and the fact that seconds must be a string not integer. It adds substantial behavioral context beyond the minimal annotations (readOnlyHint=false, destructiveHint=false), making the tool's behavior transparent.

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 well-organized with sections for async behavior, status flow, and parameter details. It is front-loaded with the most critical info (async, immediate return) and every sentence adds value without redundancy.

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?

All five parameters are explained, return fields are listed, and the async lifecycle is fully described. The absence of an output schema is compensated by explicitly stating the returned Video object fields. The description is complete for a tool of this complexity.

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?

With 0% schema_description_coverage, the description compensates fully by detailing each parameter: prompt, model choices, seconds as string with exact values, size options, and input_reference_filename usage. It also explains defaults and the requirement to match image size and format.

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 tool creates a new Sora video generation job and returns a video_id. It distinguishes from siblings by mentioning async behavior and direct the user to get_video_status and download_video for follow-up actions.

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?

It explicitly instructs when to use related tools: poll with get_video_status, download with download_video, and find reference images with list_reference_images. This provides clear context and alternative tool usage, exceeding a simple 'when to use this tool'.

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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