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voice_design

Create custom voice outputs from text prompts using the MiniMax MCP server. Specify voice characteristics and preview text to generate audio files for various applications.

Instructions

Generate a voice based on description prompts.

COST WARNING: This tool makes an API call to Minimax which may incur costs. Only use when explicitly requested by the user.

 Args:
    prompt (str): The prompt to generate the voice from.
    preview_text (str): The text to preview the voice.
    voice_id (str, optional): The id of the voice to use. For example, "male-qn-qingse"/"audiobook_female_1"/"cute_boy"/"Charming_Lady"...
    output_directory (str, optional): The directory to save the voice to.
Returns:
    Text content with the path to the output voice file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
preview_textYes
voice_idNo
output_directoryNo
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 describes key behavioral traits: it's a generative tool that makes an external API call (to Minimax), incurs potential costs, and outputs a file path. However, it doesn't mention rate limits, error handling, or authentication needs, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the purpose, followed by cost warning and parameter details. Every sentence adds value, with no wasted words. Minor points deducted for slightly dense parameter formatting, but overall it's efficient.

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 tool's complexity (external API, file output) and lack of annotations/output schema, the description does a good job covering essentials: purpose, usage warning, parameters, and return value. It could improve by mentioning file formats, error cases, or sibling tool relationships, but it's largely complete for agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all parameters: 'prompt' is for voice generation, 'preview_text' is for voice previewing, 'voice_id' includes example values, and 'output_directory' specifies where to save. This goes well beyond the bare schema, though it could provide more detail on format constraints.

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 voice based on description prompts.' It specifies the verb ('Generate') and resource ('a voice'), making the function immediately understandable. However, it doesn't differentiate from sibling tools like 'voice_clone' or 'text_to_audio,' which prevents a perfect score.

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 guidance: 'Only use when explicitly requested by the user.' This clearly defines when to use the tool (user request) and implies when not to use it (without explicit request). The cost warning further reinforces prudent usage, making this excellent 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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