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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

update_finetune

Update a music finetune's metadata and settings via ElevenLabs. Use it to rename, tag, or change visibility of an existing finetune.

Instructions

Update Music Finetune Spends ElevenLabs credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
tagsNo
visibilityNo
finetune_idYes
primary_genreNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is largely covered. The description adds a meaningful cost trait by noting that the operation spends ElevenLabs credits. However, it does not explain what mutations are allowed, permission requirements, or other side effects beyond that credit consumption.

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 very short and front-loads the core action, so it is not verbose. But the sentence is malformed and lacks clear separation between the action and the credit-spending note, which weakens structure.

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?

For an update tool with five parameters, no schema descriptions, and no output schema, the description is too thin. It gives the purpose and a credit-cost hint but leaves parameter meanings, usage conditions, and mutation details completely unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has five parameters with 0% description coverage, and the description provides no information about any of them. It does not clarify what finetune_id identifies, which fields can be updated, or what values like visibility, tags, or primary_genre mean.

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 names a specific verb and resource: 'Update Music Finetune.' That is enough to distinguish it from create_finetune, get_finetune, and delete_finetune, though the sentence itself does not explicitly say so. The trailing 'Spends ElevenLabs credits' is an odd addition but does not obscure the core action.

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 guidance about when to use this tool versus alternatives such as create_finetune or get_finetune. It implies updating an existing finetune, but never states prerequisites or when the operation is appropriate.

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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