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elevenlabs_convert_chapter_endpoint

Convert Chapter. Starts conversion of a specific chapter.

Bulk support: accepts project_ids, chapter_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
chapter_idYes
project_idYes
chapter_idsNo
project_idsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

The description reveals that the tool 'starts' a conversion, implying an asynchronous operation, but it does not explain what the conversion produces, how to track its status, what side effects occur, or what the response contains. The annotations provide only generic flags, so the description carries most of the burden and falls short.

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?

The description is very short and front-loaded, with the key information in the second sentence. The first sentence 'Convert Chapter.' is largely redundant with the tool name, so not every word earns its place, but overall the description is appropriately sized.

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 state-changing tool with no output schema and sparse annotations, the description leaves too much unspecified: no mention of conversion status/results, no polling guidance, no account/auth details, and no explanation of batch behavior beyond parameter names. The minimal description is insufficient for reliable invocation.

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?

With 0% schema description coverage, the description does add some meaning by distinguishing singular conversion ('a specific chapter') from bulk execution via 'project_ids, chapter_ids'. However, it does not clarify the relationship between the required singular fields and the batch arrays, nor does it explain the 'account' parameter.

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 clearly states the action: 'Starts conversion of a specific chapter', identifying the resource and operation. It also mentions bulk support, which adds scope. However, the opening line 'Convert Chapter.' largely repeats the tool name and it does not explicitly contrast with the sibling 'elevenlabs_convert_project_endpoint'.

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

Usage Guidelines3/5

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

The bulk-support sentence gives useful context for when to use the array parameters, implying batching is supported. However, it does not explicitly say when to prefer this tool over convert_project_endpoint or what distinguishes single vs. bulk usage beyond parameter choice.

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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