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@aiwerk/mcp-server-elevenlabs

@aiwerk/mcp-server-elevenlabs

by AIWerk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

dubbing_target_transcript_regenerate

Regenerate a dubbing project's target-language transcript using project and language IDs. This credit-spending call rebuilds the translated transcript for that target.

Instructions

Regenerate Dubbing Target Spends ElevenLabs credits.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>",
      "language_id": "<language_id>"
    },
    "name": "dubbing_target_transcript_regenerate"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_idYesIdentifier of the dubbing project.
language_idYesIdentifier of the language target.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the mutation and non-idempotence profile is partly covered. The description adds genuinely useful non-annotation context - that the call spends ElevenLabs credits - but omits whether an existing transcript is overwritten or merged, which matters given the non-destructive hint.

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

Conciseness4/5

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

A single short sentence with the verb front-loaded and zero filler; the awkward phrasing ('Regenerate Dubbing Target Spends ElevenLabs credits') is grammatically clumsy but costs little.

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 non-idempotent mutation with no output schema, the description covers the key cost side effect but leaves the most consequential unknown - whether regeneration replaces existing transcript segments or only fills gaps - unstated, which the sibling edit tools make a relevant question.

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%, with both project_id and language_id documented in the schema itself. The description adds no parameter-level information, so the baseline 3 applies.

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 names a specific verb ('Regenerate') and resource ('Dubbing Target' transcript), which distinguishes it from the sibling read tools like dubbing_target_transcript_get and the manual edit tools dubbing_target_transcript_segment_update. However, it never explicitly contrasts itself with those siblings, so an agent must infer the boundary from the name alone.

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 statement of when to use this regeneration versus manually editing segments via dubbing_target_transcript_segment_update/segments_update, and no mention of prerequisites or when-not-to-use. The only guidance is the implied cost warning.

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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