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translate_speech

Translates speech audio between English and Mandarin Chinese. Automatically detects input language and outputs original text, translation, and synthesized audio.

Instructions

Translate speech audio between English and Mandarin Chinese. Automatically detects the input language and translates to the other. Returns original text, translation, and synthesised audio as base64-encoded WAV.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_base64YesBase64-encoded WAV audio (16 kHz, mono, 16-bit recommended)
sample_rateNoSample rate of the input audio in Hz (default: 16000)
Behavior3/5

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

The description explains the core behavior: auto-language detection, bidirectional translation, and output components. However, it does not disclose potential side effects, required permissions, rate limits, or error handling. As there are no annotations, more safety context would be beneficial.

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

Conciseness5/5

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

The description is extremely concise, using two well-structured sentences. The first sentence states the action and language pair; the second adds output details. No redundant or unnecessary words.

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

Completeness4/5

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

The description sufficiently covers the tool's purpose, input format, and output structure (original text, translation, base64 audio). However, it does not specify that the translation is limited to English-Mandarin only, nor does it differentiate from the sibling translate_file, which may be relevant for similar use cases.

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?

The input schema already provides detailed descriptions for both parameters (audio_base64 format and sample rate defaults). The tool description does not add new information about the parameters beyond what the schema offers, so it meets the baseline for high schema coverage.

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 tool translates speech between English and Mandarin Chinese, with automatic language detection and output of original text, translation, and synthesized audio. However, it does not distinguish itself from the sibling tool 'translate_file', which could potentially translate speech files or text.

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?

The description provides no explicit guidance on when to use this tool versus its siblings (health_check, translate_file) or when not to use it. It does not mention any prerequisites, limitations, or preferred scenarios.

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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