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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

text_to_dialogue_full_with_timestamps

Converts multi-voice dialogue text into a single timestamped audio file via ElevenLabs, letting you align subtitles or edit recordings by exact cue time.

Instructions

Text To Dialogue With Timestamps Spends ElevenLabs credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
inputsYesA list of dialogue inputs, each containing text and a voice ID which will be converted into speech. The maximum number of unique voice IDs is 10. For reliable generation, keep the total character count across all `inputs[].text` values at or below 2,000 characters per request. Longer requests can te
model_idNoIdentifier of the model that will be used, you can query them using GET /v1/models. The model needs to have support for text to speech, you can check this using the can_do_text_to_speech property.
settingsNo
language_codeNo
output_formatNoOutput format of the generated audio. Formatted as codec_sample_rate_bitrate. So an mp3 with 22.05kHz sample rate at 32kbs is represented as mp3_22050_32. MP3 with 192kbps bitrate requires you to be subscribed to Creator tier or above. PCM and WAV formats with 44.1kHz sample rate requires you to be
enable_loggingNoWhen enable_logging is set to false zero retention mode will be used for the request. This will mean history features are unavailable for this request, including request stitching. Zero retention mode may only be used by enterprise customers.
apply_text_normalizationNoThis parameter controls text normalization with three modes: 'auto', 'on', and 'off'. When set to 'auto', the system will automatically decide whether to apply text normalization (e.g., spelling out numbers). With 'on', text normalization will always be applied, while with 'off', it will be skipped.
pronunciation_dictionary_locatorsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior3/5

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

Annotations already declare the mutation/safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false). The description adds one genuinely new behavioral fact — that the call consumes ElevenLabs credits — which is useful cost/billing context. However it omits other important traits such as synchronous blocking, latency, and the 2,000-character request limits that matter for this long-running generation.

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

Conciseness2/5

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

It is a single short sentence, but the brevity is under-specification rather than concision — half the sentence merely repeats the title. It is not front-loaded with actionable purpose information.

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

Completeness1/5

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

For a 9-parameter, credit-consuming audio generation tool with no output schema, the description is grossly incomplete: no explanation of inputs, no note about the timestamps in the response, no limits, and no differentiation from streaming or non-timestamp variants.

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 only 56%, so the description is expected to compensate for undocumented parameters (seed, settings.stability, language_code, pronunciation_dictionary_locators). It contributes nothing about any parameter, leaving gaps in both schema and description.

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 essentially restates the tool name ('Text To Dialogue With Timestamps') and adds only a credit-cost note. It never states what the tool actually produces — dialogue audio with timestamp alignment — in a way that distinguishes it from siblings like text_to_dialogue, text_to_dialogue_stream, or text_to_speech_full_with_timestamps.

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 when-to-use guidance and no mention of alternatives, despite the crowded sibling space (text_to_dialogue, text_to_dialogue_stream, text_to_dialogue_stream_with_timestamps, text_to_speech_full_with_timestamps). The agent is left to infer selection entirely.

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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