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alarconcesar

gemini-tts-mcp

by alarconcesar

list_voices

List available Gemini TTS voices with gender, tone, and description. Filter by gender or tone to find suitable voices for text-to-speech.

Instructions

List all Gemini TTS voices with gender, tone, and description.

Optionally filter by gender and/or tone. Gemini TTS voices are multilingual — any voice speaks the language of the input text.

Args: filter_gender: Filter by "male", "female" (case-insensitive). filter_tone: Filter by tone name, e.g. "Soft", "Bright", "Firm", "Warm", "Upbeat", "Clear", "Smooth", "Informative", "Easy-going", etc. (case-insensitive).

Returns: A formatted table of matching voices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filter_toneNo
filter_genderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains that voices are multilingual and can be filtered, but it does not disclose any potential behavioral traits such as pagination, rate limits, or data freshness. For a simple listing tool, this is adequate but not outstanding.

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 concise: two sentences plus clearly labeled Args and Returns sections. Every sentence adds value, and the structure is easy to parse.

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?

For a tool with only two optional parameters and an existing output schema, the description is mostly complete. It notes the return is a 'formatted table', but could be slightly more specific about the exact fields in the output. Nonetheless, it covers the essential context.

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?

Schema description coverage is 0%, yet the description adds significant value by explaining both parameters with examples and case-insensitivity. For filter_tone, it lists acceptable tone names, which is more informative than the schema alone.

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 the action ('List') and resource ('all Gemini TTS voices') and specifies that it includes gender, tone, and description. It distinguishes from sibling 'list_voices_by_gender' which likely only filters by gender, whereas this tool also supports tone filtering.

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

Usage Guidelines3/5

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

The description indicates that filtering is optional and provides examples of filter values. However, it does not explicitly state when to use this tool versus the sibling 'list_voices_by_gender', nor does it provide guidance on when not to use it.

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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