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List Dub TTS Voices

lab_dub_voices
Read-only

List the ElevenLabs TTS voices available for lab_dub_tts's voice_id — this is the EN-dub-track text-to-speech voice list, NOT a project's cloned voices (those are lab_list_voices). Reads only — no state changes, no credits. If ELEVENLABS_API_KEY isn't configured on the backend the list comes back empty and configured is false.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true; the description goes further by confirming no credits are consumed and, more importantly, disclosing the failure mode — an unconfigured ELEVENLABS_API_KEY yields an empty list plus a `configured: false` signal. That tells the agent how to distinguish "no voices exist" from "backend not configured," which the annotations cannot express.

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, front-loaded with what the tool returns and the sibling it is not, followed by the read-only/cost note and the API-key caveat. Every clause carries 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 zero-parameter, no-output-schema list tool, the description covers purpose, sibling routing, safety/cost, and the one return-value nuance that matters (`configured`). An agent has everything needed to call it and to interpret an empty response correctly.

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?

The tool takes zero parameters, so there is nothing to document and the baseline is 4. The mention of `voice_id` refers to a consuming sibling's parameter rather than this tool's input, which is helpful context but not parameter semantics for this schema.

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 the ElevenLabs TTS voices") and immediately scopes it to the consumer (lab_dub_tts's `voice_id`). It explicitly excludes the look-alike sibling by name ("NOT a project's cloned voices (those are lab_list_voices)"), so an agent can disambiguate from lab_list_voices 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?

Names both the condition for using it (populating lab_dub_tts's `voice_id`) and the alternative for the other case (lab_list_voices for cloned voices). It also gives a prerequisite-style caveat about ELEVENLABS_API_KEY, which is exactly the routing/eligibility information an agent needs before calling.

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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