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List narrator voices

list_voices
Read-only

List narrator voices (call this before create_lesson when the user names a voice, a tone or a gender)

Use when someone asks which voices exist, wants a female or male narrator, a calm or lively tone, or English narration. Returns each voice with its name, a one-sentence tone, language (tr or en), gender, accent, tier and a short audio sample. Pass a voice key to create_lesson. Optional language narrows the list. Premium voices spend 1.5x minutes. No minutes are spent here.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_voices"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoOnly voices that speak this language.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint the description discloses cost behavior that annotations cannot express: premium voices consume 1.5x minutes and this call spends none. It also enumerates the returned fields (name, tone, language, gender, accent, tier, audio sample), so the agent knows what it will get back despite there being no output schema.

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?

Front-loaded with the action and the pre-condition, then usage triggers, then return/cost facts — a logical order with no filler. The create_lesson reference recurs in two sentences (the parenthetical and "Pass a voice `key` to create_lesson"), which is mild redundancy but not wasteful.

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 single-optional-parameter, no-output-schema list tool, this covers everything an agent needs: when to call it, what it returns, the cost implication, and how to use the result downstream. Nothing material is missing.

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?

Schema coverage is 100% and the enum already documents that language restricts results, so "Optional `language` narrows the list" adds little. The genuinely new information (a voice `key` is what feeds create_lesson) concerns a different tool's parameter rather than this one's.

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?

States a specific verb and resource ("List narrator voices") and immediately positions it relative to a sibling by naming create_lesson as the consumer of the result. An agent can distinguish this read-only enumeration tool from create_lesson/get_lesson without opening any 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?

Gives concrete triggering conditions ("user names a voice, a tone or a gender") plus examples of the request shapes that select it: which voices exist, female or male narrator, calm or lively tone, English narration. It also states the sequencing rule (call before create_lesson), which is the key routing decision among these siblings.

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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