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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

get_finetunes

Read-onlyIdempotent

Fetch and filter ElevenLabs music finetunes by creator, visibility, and sort order to list or page through available finetunes.

Instructions

Get Music Finetunes

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort by field (created_at or name)
cursorNoUsed for fetching the next page. Cursor is returned in the response.
page_sizeNoHow many finetunes to return. Max 150, default 50.
created_byNoFilter by creator. 'self' returns finetunes you created; 'workspace' returns finetunes created by workspace teammates; 'elevenlabs' returns ElevenLabs curated finetunes. Omit to return finetunes from all creators.
visibilityNoFilter by visibility. 'private' returns private finetunes; 'workspace' returns workspace-shared finetunes; 'public' returns public finetunes, which are currently ElevenLabs curated finetunes. Omit to return all accessible finetunes.
sort_directionNoSort direction (asc or desc)

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, covering the safety profile fully. The description adds nothing behavioral—no mention of pagination, result scope, or auth context—so it provides no value beyond the structured annotations.

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?

At three words it is maximally short and front-loaded, with no wasted sentences. However, the brevity stems from under-specification rather than well-chosen economy, so it does not earn a top score.

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 six-parameter, paginated listing tool with no output schema, and the description says nothing about it being a paginated list, what the cursor returns, or how results are scoped. Given the moderate complexity and the rich annotation set, the description leaves key context unstated.

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

Parameters3/5

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

Schema description coverage is 100%: all six parameters (sort, cursor, page_size, created_by, visibility, sort_direction) are thoroughly documented in the schema, including enum meanings. The description adds no parameter meaning beyond that, so the baseline 3 is appropriate.

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?

"Get Music Finetunes" essentially restates the tool name and title, adding only the word "Music." It does not distinguish this list tool from siblings like get_finetune (singular), create_finetune, update_finetune, or delete_finetune. An agent learns only that it retrieves something related to finetunes, with no scope or filtering detail.

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 indication of when to use this tool versus get_finetune, the update/delete/create finetune siblings, or any other listing tool. No prerequisites or exclusions are given, so the agent must infer usage from the name alone.

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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