elevenlabs_text_to_speech

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output format (base64 audio) but does not disclose rate limits, authentication requirements, or potential side effects (e.g., cost per character). The description is insufficient for a tool with external API calls.

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 extremely concise with only two sentences, front-loading the action and output format. No extraneous information.

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 9 parameters, no output schema, and no annotations, the description is too sparse. It doesn't explain how to obtain a voice_id, doesn't mention the need for an API key, and doesn't clarify the structure of the base64 output. The tool is complex but the description is minimal.

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?

The description adds no parameter semantics beyond what is in the input schema. The schema already covers 6 of 9 parameters with descriptions (67% coverage). The description does not explain parameter relationships or provide guidance on picking voice_id or model_id.

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 action ('Convert text to speech'), the resource ('selected ElevenLabs voice'), and the output format ('Returns base64-encoded audio'). It distinguishes itself from sibling tools like elevenlabs_list_voices or elevenlabs_get_voice by specifying the conversion functionality.

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?

No guidance is provided on when to use this tool versus alternatives like elevenlabs_get_voice or elevenlabs_get_history. There is no mention of prerequisites (e.g., need for a valid voice_id from list_voices) or context for choosing models or parameters.

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