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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

transcribe

Converts selected dubbing segments into text, spending ElevenLabs credits; deprecated upstream.

Instructions

Transcribes Segments Spends ElevenLabs credits. Deprecated upstream.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
segmentsYesTranscribe this specific list of segments.
dubbing_idYesID of the dubbing project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior4/5

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

Annotations declare the safety profile (readOnly=false, destructive=false, idempotent=false, openWorld=true), so the bar is lower, and the description still adds two things structured fields cannot: it consumes ElevenLabs credits and it is deprecated upstream. Both are material to a calling agent weighing cost and lifecycle. It stops short of saying what the transcription returns or what happens to the segment list.

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 payload is short and the cost/deprecation facts are front-loaded, which is good. However the two sentences are malformed and jammed together ("Segments Spends"), which slows parsing rather than helping it. Brevity is not the problem; clarity is.

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?

There is no output schema, so the description carries the return-value burden, and it says nothing about what transcription output the caller gets back. It does at least flag credit consumption and deprecation, which are the two most decision-relevant facts for this mutating tool.

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% — both dubbing_id and segments are documented in the schema, including that segments is the specific list to transcribe. The description adds nothing beyond that, so the baseline 3 applies.

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 reads as two fragments run together ("Transcribes Segments Spends ElevenLabs credits. Deprecated upstream."), so the stated purpose is little more than the tool name plus a parameter name. It never distinguishes this from the many sibling transcription tools (speech_to_text, dubbing_target_transcript_get, dubbing_target_transcript_regenerate), leaving the agent to guess which transcription path applies.

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?

"Deprecated upstream" is a useful steer away from the tool, but no positive when-to-use guidance or alternative is named. With dozens of transcription/dubbing transcript siblings, the agent gets no help deciding whether to call this at all versus a non-deprecated equivalent.

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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