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elevenlabs_text_to_speech

Converts text to speech using ElevenLabs voices, returning base64-encoded audio for integration.

Instructions

Convert text to speech with a selected ElevenLabs voice. Returns base64-encoded audio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYes
voice_idYes
textYesText to synthesize (max 5000 characters)
model_idNoElevenLabs model ID (default: eleven_monolingual_v1)
output_formatNomp3_44100_128, pcm_16000, etc. (default: mp3_44100_128)
stabilityNo0.0-1.0 (default: 0.5)
similarity_boostNo0.0-1.0 (default: 0.75)
styleNo0.0-1.0 style exaggeration
use_speaker_boostNo
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It states the output is base64-encoded audio, which is helpful, but omits information about rate limits, API usage costs, potential latency, or that the required api_key must be valid. The tool has 9 parameters, so more behavioral context is needed.

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 two sentences, placing the core purpose first and then the output format. It is efficient, but could include more information without becoming too long. The structure is good for quick scanning.

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?

The tool has 9 parameters, no annotations, and no output schema. The description is too brief to fully inform the agent about authentication (api_key), voice selection requirements, or parameter meanings. Given its complexity, the description should be more comprehensive to enable correct invocation.

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

Parameters2/5

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

Schema description coverage is 67%, meaning some parameters lack descriptions. The tool description adds no parameter details (e.g., what stability or similarity_boost do), so it fails to compensate for the gap. The three required parameters (api_key, voice_id, text) are not explained, leaving the agent to infer their meaning from names.

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

Purpose5/5

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

The description clearly states the tool converts text to speech using an ElevenLabs voice, which distinguishes it from sibling tools like elevenlabs_get_voice or elevenlabs_list_voices. It also specifies the output format (base64-encoded audio), leaving no ambiguity about the action.

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 description implies you need a voice_id but does not explicitly say to first use elevenlabs_list_voices to get available voices. It lacks guidance on prerequisites, when to use this tool versus alternatives, or when not to use it (e.g., if only text input is needed).

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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