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Create speech

create_speech

Generates audio from input text using multiple TTS models with customizable voice, speed, and format options.

Instructions

Create speech Generates audio from the input text (Text-to-Speech).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesText to synthesize.
modelNoTTS model. Query GET /v1/models?recommended_for=tts for the current shortlist.tts-1
speedNoSpeech speed for model families that support it.
voiceNoVoice selector for OpenAI-compatible, Gemini, xAI, and MiniMax-compatible routes. Some MiniMax routes also accept voice_id.
promptNoOptional speaking style prompt for Gemini TTS models.
voice_idNoProvider-native voice selector for MiniMax-compatible speech models.
temperatureNoSampling temperature for Gemini-compatible TTS routes.
instructionsNoOptional style or delivery instructions for OpenAI-compatible TTS models that support them.
language_codeNoOptional language code for Gemini, xAI, and compatible TTS routes.
stream_formatNoTokenLab delivery format. stream_format=sse is not supported for tts-1 or tts-1-hd.audio
response_formatNoAudio format. Common values include mp3, opus, aac, flac, wav, and pcm. Supported values vary by model family.
Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, so the description need not re-state safety. The description adds that it generates audio, but lacks details on output delivery (e.g., stream, file) or side effects like rate limits.

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

Conciseness3/5

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

The description is short but includes a redundant phrase 'Create speech' before the actual explanation. It could be more concise by removing the duplication.

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?

Given 11 parameters and no output schema, the description fails to explain what the output is (e.g., file ID, stream, URL), how to access it, or any post-creation steps. This leaves the agent uncertain about the tool's result.

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% with detailed parameter descriptions. The tool description adds no additional parameter semantics, so baseline 3 is appropriate.

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 states 'Generates audio from the input text (Text-to-Speech)', which clearly identifies the verb (generates) and resource (audio from text). It is distinct from siblings like transcribe_audio or create_music, though no explicit differentiation is provided.

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?

No guidance on when to use this tool versus alternatives such as transcribe_audio or other creation tools. There is no mention of prerequisites, use cases, or exclusions.

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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