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MCPGeneration-for-ElevenLabs

MCPGeneration-for-ElevenLabs

generate_dialogue

Creates multi-voice dialogue audio from ordered text and voice inputs while validating voice and length limits; paid authorization is required.

Instructions

Generate a multi-voice dialogue in input order. Enforces the documented unique voice and length limits. Paid authorization is required.

Input Schema

NameRequiredDescriptionDefault
inputsYes
filenameYes
model_idNo
allow_paidNo
future_textNo
language_codeNo
output_formatNomp3_44100_128
previous_textNo
allow_unknown_costNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses input-order processing, unique-voice and length-limit enforcement, and paid authorization, but it does not explain what those limits are, what happens when they are violated, or how cost-related flags behave.

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?

The description is short, front-loaded, and free of filler. However, the phrase 'documented unique voice and length limits' points to documentation that is not present, reducing its practical value.

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?

This is a complex nine-parameter generation tool with no annotations, no output schema, and no schema descriptions. The description is too thin to fully prepare an agent to invoke it correctly, especially regarding optional parameters, cost behavior, and output expectations.

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 0% across nine parameters, so the description must compensate. It only vaguely references inputs, voice uniqueness, length limits, and paid authorization, leaving filename, model_id, language_code, output_format, previous_text, future_text, and allow_unknown_cost unexplained.

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 states a specific verb and resource: generate a multi-voice dialogue, with input order called out. It is clear enough to distinguish from single-voice speech tools, but it does not explicitly differentiate from sibling dialogue variants such as generate_dialogue_stream or generate_dialogue_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?

The description gives no guidance on when to use this tool versus the many sibling dialogue and speech tools. It mentions paid authorization, but that is a prerequisite rather than a usage-selection rule.

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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