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generate_video

Create custom videos using text prompts with MiniMax MCP JS. Specify model, duration, resolution, and output directory to generate videos tailored to your needs. Supports async mode for task management.

Instructions

Generate a video based on text prompts.

Note: This tool calls MiniMax API and may incur costs. Use only when explicitly requested by the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncModeNoWhether to use async mode. Defaults to False. If True, the video generation task will be submitted asynchronously and the response will return a task_id. Should use `query_video_generation` tool to check the status of the task and get the result.
durationNoThe duration of the video. The model must be "MiniMax-Hailuo-02". Values can be 6 and 10.
firstFrameImageNoFirst frame image
modelNoModel to use, values: ["T2V-01", "T2V-01-Director", "I2V-01", "I2V-01-Director", "I2V-01-live", "MiniMax-Hailuo-02"]MiniMax-Hailuo-02
outputDirectoryNoThe directory to save the output file. `outputDirectory` is relative to `MINIMAX_MCP_BASE_PATH` (or `basePath` in config). The final save path is `${basePath}/${outputDirectory}`. For example, if `MINIMAX_MCP_BASE_PATH=~/Desktop` and `outputDirectory=workspace`, the output will be saved to `~/Desktop/workspace/`
outputFileNoPath to save the generated video file, automatically generated if not provided
promptYesText prompt for video generation
resolutionNoThe resolution of the video. The model must be "MiniMax-Hailuo-02". Values range ["768P", "1080P"]
Behavior4/5

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 effectively adds context beyond basic functionality: it discloses that the tool 'calls MiniMax API and may incur costs,' which informs about external dependencies and financial implications. However, it doesn't cover other behavioral aspects like rate limits, error handling, or output format, preventing a perfect score.

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second sentence adds crucial usage and cost notes. Every sentence earns its place with no wasted words, making it highly efficient for an AI agent.

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 complexity (8 parameters, no output schema, no annotations), the description is reasonably complete. It covers purpose, usage constraints, and cost implications, which are critical for this type of tool. However, it lacks details on output (e.g., what is returned, file format) and error handling, which would be needed 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?

The schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond the schema. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description, which applies here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 a video based on text prompts.' It specifies the verb ('generate'), resource ('video'), and input type ('text prompts'). However, it doesn't explicitly distinguish this from sibling tools like 'image_to_video' or 'text_to_image', which would require a 5.

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?

The description provides explicit usage guidelines: 'Use only when explicitly requested by the user.' This clearly indicates when to use the tool (user request) and implies when not to use it (without explicit request). It also mentions cost implications ('may incur costs'), adding practical 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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