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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

convert_project_endpoint

Convert an ElevenLabs Studio project by project_id, spending credits to complete the conversion.

Instructions

Convert Studio Project Spends ElevenLabs credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesThe ID of the Studio project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already establish non-read-only, non-idempotent, open-world behavior, and the description usefully adds the credit-consumption cost trait that annotations do not cover. It does not disclose what conversion produces, whether it is reversible, or whether it can be re-run without incurring further spend.

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?

A single short sentence with no filler and the key cost fact included. It reads as slightly truncated/awkward ('Convert Studio Project Spends ElevenLabs credits'), which costs it the top mark, but it is front-loaded and economical.

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 a non-idempotent, credit-consuming, open-world operation with no output schema, the description should tell the agent what the conversion yields and what to expect afterward. It omits the outcome, the cost magnitude, and any post-conditions, leaving the agent unable to predict the effect of the call.

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 coverage is 100% and the single project_id parameter is fully documented in the schema, so the baseline of 3 applies. The description adds no format, sourcing, or constraint detail beyond what the schema already provides.

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 gives a verb ('Convert') and a resource ('Studio Project'), so the general action is identifiable, but it never states what the project is converted into or what the result is. The sibling convert_chapter_endpoint suggests a family of conversion operations, yet nothing here explains how this one differs (project-level vs chapter-level).

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 explicit guidance on when to invoke this versus alternatives such as convert_chapter_endpoint, edit_project, or get_project_by_id. The only usage-adjacent signal is that credits are consumed, which the agent must infer as a caution rather than being told when or when not to call it.

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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