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luma_generate_video

Generate AI videos from text descriptions. Describe the scene, motion, style, and mood to create high-quality videos without reference images.

Instructions

Generate AI video from a text prompt using Luma Dream Machine.

This is the simplest way to create video - just describe what you want and Luma
will generate a high-quality AI video.

Use this when:
- You want to create a video from a text description
- You don't have reference images
- You want quick video generation

For using reference images (start/end frames), use luma_generate_video_from_image instead.

Returns:
    Task ID and generated video information including URLs, dimensions, and thumbnail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate. Be descriptive about the scene, motion, style, and mood. Examples: 'A cat walking through a garden with butterflies', 'Astronauts shuttle from space to volcano', 'Ocean waves crashing on a beach at sunset'
aspect_ratioNoVideo aspect ratio. Options: '16:9' (landscape, default), '9:16' (portrait), '1:1' (square), '4:3', '3:4', '21:9' (ultrawide), '9:21'.16:9
loopNoIf true, generate a looping video where end connects seamlessly to start. Default is false.
enhancementNoIf true, enable clarity enhancement for the video. Default is true.
timeoutNoTimeout in seconds for the API to return data. Default is 300.
callback_urlNoWebhook callback URL for asynchronous notifications. When provided, the API will call this URL when the video is generated.

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 mentions return values, but does not disclose async nature, generation time, or any side effects. The timeout parameter hints at long duration, but description implies immediate return. Could be more 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?

Concise yet comprehensive: single line for purpose, explanatory paragraph, bullet list for usage, explicit alternative, and return format. No wasted words.

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?

With output schema available, description adequately covers return values. All 6 parameters have schema descriptions. Sibling tools are referenced. Lacks only async workflow details, but still fully functional.

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 coverage is 100%, so each parameter is already described. The description adds only minor context (like prompt examples) but nothing significant beyond the schema. Baseline 3 is appropriate.

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?

Clearly states 'Generate AI video from a text prompt' with specific verb and resource. Explicitly distinguishes from sibling tool luma_generate_video_from_image by stating when to use each.

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?

Provides explicit 'Use this when:' bullet list and directly tells when not to use it (have reference images), naming the alternative tool. Complete guidance.

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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