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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

compose_detailed_stream

Generate and stream custom music from text prompts or composition plans, returning detailed audio responses. Requires ElevenLabs credits.

Instructions

Stream Composed Music With A Detailed Response Spends ElevenLabs credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
promptNo
model_idNo
finetune_idNo
lyrics_textNo
music_promptNoComposition plan for the `music_v1` model. Using this field with any other model will result in an error.
output_formatNoOutput format of the generated audio. Formatted as codec_sample_rate_bitrate. Use "auto" (the default) to let the API pick the best format for the selected model: mp3_44100_128 for v1 models and mp3_48000_192 for v2 models.
generation_modeNo
music_length_msNo
with_timestampsNoWhether to return the timestamps of the words in the generated song.
composition_planNo
finetune_strengthNoHow strongly the finetune influences the generation. Defaults to 1.0 (full strength). Lower values soften the influence of the finetune, leaving more room for prompt-level steering. Only meaningful when `finetune_id` is also provided.
force_instrumentalNoIf true, guarantees that the generated song will be instrumental. If false, the song may or may not be instrumental depending on the `prompt`. Can only be used with `prompt`.
use_phonetic_namesNoIf true, proper names in the prompt will be phonetically spelled in the lyrics for better pronunciation by the music model. The original names will be restored in word timestamps.
store_for_inpaintingNoWhether to store the generated song for inpainting.
with_waveform_visualNoWhether to return the visual waveform of the generated song.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2/5.0
Behavior3/5

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

With annotations provided (readOnlyHint=false, idempotentHint=false, destructiveHint=false, openWorldHint=true), the description notes it spends credits but adds little beyond that. It doesn't describe streaming behavior, response format, or the 'detailed response' mentioned. With annotations covering safety, this is a moderate gap.

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?

A single sentence with awkward capitalization, but it is brief. However, conciseness here comes at the cost of under-specification rather than efficiency.

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?

Given 16 parameters, no output schema, partial schema coverage, and complex music composition functionality, the description is grossly inadequate. It doesn't explain streaming, detailed responses, parameter interactions, or credit costs beyond the vague mention.

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?

16 parameters with 50% schema coverage, and the description adds zero parameter information. Many parameters lack descriptions in the schema (seed, prompt, model_id, finetune_id, lyrics_text, generation_mode, music_length_ms, composition_plan), so the description should compensate but doesn't.

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 'Stream Composed Music With A Detailed Response Spends ElevenLabs credits' restates the tool name rather than explaining its actual behavior. While it implies music composition with streaming, it doesn't distinguish this tool from close siblings like compose_detailed, compose_plan, compose_detailed_stream, or stream_compose. It's more tautology than differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no alternatives mentioned, no conditions for selection. Despite having siblings like compose_detailed, compose_plan, and stream_compose, the description offers no routing information.

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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