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design_voice

Create voice previews from a text description, save audio, and retain a voice permanently using its generated ID.

Instructions

Design candidate voices from a text description (Voice Design).

Generates preview voices and saves each preview's audio to a file. To keep a preview permanently, call create_voice_from_preview with its generated_voice_id.

Args: voice_description: description of the desired voice, e.g. "an old British narrator with a warm, gravelly tone". text: sample text to speak in the previews (>=100 chars recommended). model_id: voice-design model id (API default when omitted). auto_generate_text: let ElevenLabs generate the preview text.

Returns JSON listing each preview's generated_voice_id and saved audio path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNo
model_idNo
voice_descriptionYes
auto_generate_textNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses that previews are generated and saved to files, and that they are not permanent unless explicitly saved via sibling. No annotations exist, so description covers key behaviors. Could be more explicit about the temporary nature of previews.

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?

Structured into title, paragraph, Args list, and Returns line. No redundant information. Every sentence adds value.

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 an output schema present, the description offers adequate return information (IDs and paths). Covers main purpose, parameters, and follow-up action. Lacks error handling or edge cases, but acceptable for a design tool.

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

Parameters5/5

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

Adds meaning to all four parameters beyond the schema: provides example for voice_description, recommendation for text, default behavior for model_id, and explanation for auto_generate_text. Fully compensates for 0% schema description coverage.

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 the tool designs candidate voices from a text description, generates previews, and saves audio. Distinguishes from sibling tool create_voice_from_preview which is used for permanent retention.

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?

Explicitly describes when to use (designing voices from description) and provides an alternative (use create_voice_from_preview to keep permanently). Also recommends minimum text length.

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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