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MCPGeneration-for-ElevenLabs

MCPGeneration-for-ElevenLabs

generate_dialogue_stream

Streams multi-voice dialogue through the documented ElevenLabs endpoint and saves the completed audio response to a local file.

Instructions

Call the documented streaming endpoint for a multi-voice dialogue and save the completed response locally.

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

C2.3/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It hints at saving a completed response locally, but does not disclose cost/paid-generation behavior implied by allow_paid and allow_unknown_cost, whether the call blocks until the stream completes, auth needs, rate limits, or what is overwritten at filename.

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 tight sentence with no wasted words, but its brevity reflects under-specification rather than disciplined conciseness, and it is front-loaded with a vague pointer to external documentation.

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, cost-gated, streaming multi-voice generation tool with no annotations and no output schema, the description is far too thin. It leaves an agent unable to call it correctly without external docs, which is precisely the resource it offloads to but does not summarize.

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 9 parameters, so the description must compensate and largely does not. It only weakly implies filename means local save and that dialogue is multi-voice, leaving model_id, allow_paid, allow_unknown_cost, future_text, previous_text, language_code, and output_format entirely unexplained.

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

Purpose3/5

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

The description states a verb (call), the resource (multi-voice dialogue), and the streaming variant plus local save. However, 'the documented streaming endpoint' is an indirect pointer, and it never distinguishes itself from the very similar siblings generate_dialogue and generate_dialogue_stream_with_timestamps, so an agent can't fully disambiguate from the sentence 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 when-to-use, when-not-to-use, or alternative guidance. Given four closely related dialogue/speech siblings (generate_dialogue, generate_dialogue_with_timestamps, generate_dialogue_stream_with_timestamps), the absence of routing guidance is a real gap.

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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