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

With all annotation hints set to false, the description must carry the burden of revealing behavior. It describes the output (previews with base64 audio) and implies the tool does not itself create the final voice, but it does not explicitly state side effects, rate limits, authentication requirements, or whether any persistent state is modified. It adds some context (bulk support, workflow) but leaves key behavioral aspects unaddressed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the purpose. It has two clear parts: the main purpose and output description, and a note on bulk support. There is slight redundancy in 'Design A Voice..' and 'Design a voice via a prompt.' but overall it is efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of 19 parameters and no output schema, the description provides some essential context: it explains the return value (list of previews with generated_voice_id and base64 audio) and the intended workflow. However, it lacks details on parameter usage, possible error conditions, and any side effects, making it insufficient for a tool of this complexity. It is not completely inadequate but has clear gaps.

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

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

Schema description coverage is 0%, so the description must substantially explain parameter semantics. It only mentions voice_description implicitly and highlights bulk-related parameters (model_ids, remixing_session_ids, remixing_session_iteration_ids). The other 16 parameters (e.g., seed, quality, output_format, guidance_scale) are not explained, leaving agents to guess their roles. This falls far short of compensating for the missing schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool designs a voice via a prompt and returns voice previews. It distinguishes itself from sibling tools by describing its specific output (previews with generated_voice_id) and the follow-up workflow to create a voice using the /v1/text-to-voice endpoint. This is a specific verb+resource with enough detail to differentiate from related tools.

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

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

The description provides clear context on when to use this tool: when a voice needs to be designed via a prompt and previews are needed before finalizing. It also explains the next step (using the generated_voice_id with a separate endpoint). However, it does not explicitly mention when not to use it or compare with alternatives like elevenlabs_text_to_voice_preview_stream or elevenlabs_text_to_voice_remix, so it lacks exclusionary guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.