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minimax_generate_video_from_text

Turn text into a MiniMax H3 video with custom aspect ratio, duration, and resolution. Describe scene, motion, camera, and style to generate the clip.

Instructions

Generate a MiniMax H3 video from a text prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoReturn a task_id immediately for minimax_get_task polling.
modelNoMiniMax H3 model name.MiniMax-H3
ratioNoOutput aspect ratio.16:9
promptYesScene, motion, camera, and style description.
durationNoInteger output duration from 4 to 15 seconds.
resolutionNoOutput resolution: 768P or 2K.2K
callback_urlNoOptional public webhook URL for the final result.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that a video is generated, offering no information about asynchronous execution, task creation, return values, rate limits, or the need to poll for completion. This is minimal and leaves important operational behavior undisclosed.

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 a single sentence that immediately states the core purpose and front-loads the key information. There is no filler or redundant repetition of the tool name; every word contributes to understanding what the tool does.

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?

The tool has a rich schema and output schema, so parameter details are already covered. However, the description does not mention the async/task-polling workflow or distinguish itself from the generic minimax_generate_video sibling. It is minimally viable but lacks contextual guidance for a multi-step video generation workflow.

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?

The input schema covers all 7 parameters with descriptions, including prompt, ratio, duration, resolution, async, model, and callback_url. Baseline is 3 for high schema coverage. The description itself adds no additional meaning beyond what the schema already documents, so no higher score is warranted.

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 a MiniMax H3 video from a text prompt,' naming the specific verb (generate), the resource (MiniMax H3 video), and the input type (text prompt). This distinguishes it from sibling tools like minimax_generate_video_from_images and minimax_generate_video_from_audio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as minimax_generate_video_from_images or minimax_generate_video. It does not mention async behavior, nor that results should be polled via minimax_get_task. Usage is only implied by the tool name rather than explicitly stated.

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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