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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

dubbing_language_list

Read-onlyIdempotent

List dubbing language targets for a project. Filter by status to check queued, processing, or completed translations and paginate results.

Instructions

List Dubbing Language Targets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoPass the `next_cursor` from a previous response to fetch the page after it. Omit for the first page.
statusNoFilter to targets in this status: `queued`, `processing`, `completed`, `stale`, or `failed`. Omit to return every status.
page_sizeNoNumber of language targets per page. Clamped to between 1 and 100 rather than rejected, so a larger value returns a full page.
project_idYesIdentifier of the parent dubbing project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and openWorld, so the safety profile is covered structurally. The description adds nothing about pagination behavior, result ordering, or scoping beyond what annotations provide.

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 a single short phrase with no wasted words, which satisfies conciseness, but the terseness borders on under-specification rather than efficient front-loading of useful information.

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 four-parameter, paginated list tool with no output schema, the description should indicate what a language target is and how pagination/scoping works. None of that context is present, leaving the definition inadequate despite the rich schema.

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 description coverage is 100%, and the schema documents cursor, status, page_size, and project_id thoroughly (including clamping and enum-like status values). Per the rubric, the baseline is 3 when the schema does the heavy lifting; the description contributes nothing additional.

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

Purpose2/5

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

The description 'List Dubbing Language Targets' merely restates the tool name (dubbing_language_list) and title, adding no distinguishing detail. It does convey a read verb and resource, but it is effectively a tautology rather than a clarifying statement.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives such as dubbing_language_get, dubbing_project_list, or dubbing_language_create. The agent must infer usage entirely from the name.

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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