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clone_voice

Create a Google voice clone from reference speech and spoken consent.

    Requires the user's explicit ownership/permission confirmation. Obtain
    the required consent wording with get_voice_consent_script. Inputs are
    local paths in stdio or public HTTPS URLs hosted. Returns voice_id for
    preview_voice and synthesize_audio. For a saved ElevenLabs clone from
    original video speech, use create_byo_voice with clip_reference=true.
    

Input Schema

NameRequiredDescriptionDefault
consent_pathYes
language_codeNo
reference_pathYes
confirm_ownershipNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the consent/ownership gate, the input-location constraint (local paths in stdio or public HTTPS URLs), and the returned voice_id. It stops short of failure modes, rate limits, or what happens if consent validation fails, so it is strong but not exhaustive.

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 core action and consent requirement are front-loaded, followed by input constraints, the return value, and the sibling alternative. Every sentence adds distinct information with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a four-parameter mutation tool with an output schema, the description covers the consent gate, input formats, the return value, and the sibling alternative. The only gap, language_code, is minor and the output schema handles return-value detail.

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 coverage is 0%, so the description must compensate, and it does for three of four parameters: reference_path is the reference speech, consent_path is the spoken consent, and confirm_ownership is the explicit ownership/permission confirmation. language_code is never mentioned, leaving one parameter undocumented in both schema and description.

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 opens with a specific verb and resource ('Create a Google voice clone from reference speech and spoken consent') and explicitly distinguishes itself from the sibling create_byo_voice, which handles ElevenLabs clones from video speech. An agent can route between the two without opening either schema.

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?

It states the prerequisite (explicit ownership/permission confirmation), names the helper tool to obtain the consent wording (get_voice_consent_script), and gives an explicit alternative with its condition (create_byo_voice with clip_reference=true for saved ElevenLabs clones). When-to-use and when-not-to-use are both covered.

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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