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veo_text_to_video

Generate AI video from a text description. Use to create original video clips from scratch with full creative control over scene, action, and style.

Instructions

Generate AI video from a text prompt using Veo.

This creates a video from scratch based on your text description. Veo
will interpret your prompt and generate a matching video clip.

Use this when:
- You want to create a video from a text description
- You don't have a reference image to use
- You want maximum creative freedom for Veo

For video generation starting from an image, use veo_image_to_video instead.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate. Be descriptive about scene, subject, action, camera movement, lighting, and style. Examples: 'A white ceramic coffee mug on a glossy marble countertop, steam rising, soft morning light', 'Cinematic drone shot over a forest at sunset, golden hour lighting'
modelNoVeo model version. 'veo2' for quality mode, 'veo2-fast' for faster generation. 'veo3'/'veo31' offer improved quality. Models with '-fast' suffix are faster but slightly lower quality.veo2
aspect_ratioNoVideo aspect ratio. '16:9' for landscape/widescreen, '9:16' for portrait/vertical, '1:1' for square, '4:3' for standard, '3:4' for portrait standard.16:9
translationNoIf true, automatically translate the prompt to English for better generation quality. Useful for non-English prompts.
resolutionNoVideo resolution. Options: '4k' for highest quality, '1080p' for standard HD, 'gif' for animated GIF format. If not specified, uses the model's default resolution.
callback_urlNoOptional URL to receive a POST callback when generation completes. The callback will include the task_id and video results.

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 bears full responsibility. It states that Veo interprets the prompt and generates a video, and mentions the return of a task ID and video info. However, it lacks details on latency, permissions, rate limits, or error handling, which are important for a generation tool.

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: a summary paragraph, a usage list, an alternative tool note, and a returns line. Every sentence is informative without redundancy.

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 the presence of an output schema (inferred from context signals), the description adequately covers the core functionality. It mentions the return type (task ID and video info). However, it omits limitations like maximum prompt length or video duration, which would be helpful for full completeness.

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?

Input schema coverage is 100%, with all six parameters described in the schema. The description does not add significant meaning beyond what the schema already provides, such as example usage or parameter relationships. It meets the baseline of 3.

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's purpose: 'Generate AI video from a text prompt using Veo.' It identifies the verb (generate) and resource (video from text prompt), and explicitly distinguishes from the sibling tool 'veo_image_to_video' by directing users when to use the alternative.

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 description provides a 'Use this when:' section with three specific bullet points, and explicitly mentions the alternative tool for image-based generation. However, it does not mention any prerequisites, limitations, or when to avoid using this tool (beyond the image case).

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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