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List voices

list_voices
Read-only

List the narration voices of the Revid voice picker (gender, accent, age, language, preview URL) to pick voice.voiceId for render_video. The account's cloned voices come first.

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
ageNoe.g. young, middle aged.
limitNoMaximum voices returned. Default 100.
accentNoe.g. american, british.
genderNo
searchNoWords to find in the name or description, e.g. calm, deep.
categoryNopremade (default): Revid's curated voices. all: the whole public catalog.
languageNoLanguage code, e.g. en, fr.

Output Schema

NameRequiredDescriptionDefault
okYes
dataNo
errorNo
methodYes
statusYes
endpointYes
retryAfterSecondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/non-destructive/closed-world, so the description is not carrying the safety burden. It adds genuine behavioral context beyond those annotations: the attributes returned (gender, accent, age, language, preview URL) and the ordering rule that the account's cloned voices come first, which affects how an agent should pick a default voice. It does not mention pagination or total-count behavior despite a `limit` param.

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?

Two sentences, both earning their place: the first establishes scope and the consumption target, the second delivers the ordering caveat. Front-loaded and free of filler.

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, full annotation coverage, and 86% schema description coverage, the description covers what the structured fields cannot: why the tool exists and how results are ordered. Minor gaps (pagination behavior, default category effects on result set) remain but are low-cost for a read-only list tool.

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 86%, so the schema already documents nearly every filter, and the baseline is 3. The description lists gender/accent/age/language as voice attributes but does not disambiguate them as combinable filters, and says nothing about `category`, `search`, or `limit` beyond what the schema states, so it adds little semantic value.

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?

Specific verb + resource ("List the narration voices of the Revid voice picker") plus an explicit downstream purpose: choosing `voice.voiceId` for `render_video`. This makes it unmistakable versus siblings like `clone_voice` or `list_characters`.

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

Usage Guidelines4/5

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

The description states clearly when to reach for it — to pick a voiceId to feed `render_video` — which is a real routing signal. It stops short of explicit exclusions (e.g. that it does not create or clone voices; that is `clone_voice`), so it is clear context without full when-not 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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