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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

dubbing_language_create

Add a new target language to a dubbing project by providing the project ID and BCP-47 language tag. This action spends ElevenLabs credits.

Instructions

Create Dubbing Language Target Spends ElevenLabs credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesIdentifier of the parent dubbing project.
translationsNo
voice_settingsNo
target_languageYesBCP-47 language tag to dub the project into (for example, `fr` or `es-MX`). Must be one of the [languages the project's dubbing model supports](https://elevenlabs.io/docs/help-center/product/dubbing/which-languages-are-supported-in-dubbing), and a region-qualified tag must be one of the supported di

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=false, and openWorldHint=true. The description adds a useful behavioral detail: it spends ElevenLabs credits. It does not explain what a Dubbing Language Target is, whether repeated calls duplicate resources, or what permissions are required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loads the action, but it is ungrammatical and fragmented: 'Create Dubbing Language Target Spends ElevenLabs credits.' It is concise but under-specified for a tool that creates a resource and incurs cost.

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

Completeness2/5

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

For a mutation tool that requires project_id and target_language and spends credits, the description is far too sparse. It does not explain the effect on the dubbing project, return value, or any constraints beyond the implicit cost warning.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50%, with 'translations' having no description at all. The description provides no parameter meaning, so it does not compensate for the schema gap. The agent must rely entirely on the schema for project_id, target_language, translations, and voice_settings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Create Dubbing Language Target.' This distinguishes it from sibling tools like dubbing_language_get, dubbing_language_list, and dubbing_language_delete. It does not mention the parent project or scope, but the core purpose is clear.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus alternatives. The only hint is that it 'Spends ElevenLabs credits,' which is a cost warning rather than usage direction. No prerequisites or exclusions are given.

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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