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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

dub

Generates translated audio for all or selected segments and languages in an ElevenLabs project; consumes credits. Deprecated upstream.

Instructions

Dubs All Or Some Segments And Languages Spends ElevenLabs credits. Deprecated upstream.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
segmentsYesDub only this list of segments.
languagesYes
dubbing_idYesID of the dubbing project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior4/5

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

The description adds real behavioral context beyond the annotations: it consumes ElevenLabs credits (a cost side effect that idempotentHint=false and destructiveHint=false do not convey) and it is deprecated upstream, which is decision-relevant. It stops short of describing auth requirements or partial-failure behavior, so not a 5.

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?

It is short and front-loads the action, which is good, but the sentence is a garbled run-on with stray title casing that forces the reader to re-parse it. Being terse is not the same as being economical when the single sentence is ambiguous.

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

Completeness3/5

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

For a 3-required-parameter mutating tool with no output schema, the description covers the two highest-value facts (credit spend, deprecation) but omits what the call actually returns and how segments/languages should be populated. Adequate, but several gaps remain for a paid mutation.

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 67%: segments and dubbing_id are described in the schema, while languages has no schema description. The phrase 'All Or Some Segments And Languages' vaguely implies optional filtering, but the description adds essentially no format or semantics beyond what the schema already provides, so the baseline 3 applies.

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

Purpose3/5

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

It names a verb (dubs) and the resource being modified (segments and languages of a dubbing project), so the core action is inferable. However, the run-on title-case phrasing is garbled, and it gives no differentiation from the many sibling dubbing tools (create_dubbing, migrate_segments, dubbing_project_*), so an agent cannot easily place it in the family.

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 a weak implicit signal — 'Deprecated upstream' hints the tool may be avoided — but it never says when to use this versus create_dubbing or the dubbing_language_* tools, nor what 'All Or Some' means as a selection condition. No prerequisites or alternatives are named.

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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