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by io.github.code0xff
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Text-to-speech: MeloTTS MP3 in 6 languages (en, ko, ja, zh, es, fr), safety-screened

ai_tts

Use when an agent needs spoken audio from short text (voice reply, narration, accessibility). Input: text (max 500 chars), lang (en, ko, ja, zh, es, fr; default en). Output: JSON with an MP3 (base64), voice, model, safety verdict. Fixed built-in voices, no voice cloning. Text screened by Llama Guard 3; unsafe 422, not charged. Not stored. Example: ?text=Hello%20from%201gateway&lang=en Price: $0.004 USDC (Base or Solana) via x402.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "ai_tts"
  }
}

Input Schema

NameRequiredDescriptionDefault
langNoSpeech language (default en); one built-in voice per language
textYesText to speak (1-500 chars). Empty or longer text → 400 before payment (not charged)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

No annotations are provided, so the description carries full burden and does so richly: Llama Guard 3 screening, unsafe text returns 422 and is not charged, no storage, fixed voices, and the pricing/billing model via x402. These are behavior facts an agent cannot get from the schema.

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?

Front-loaded with the use condition, then input, output, safety, and price in a tight sequence. Dense but every sentence carries information; the example and price line are slightly telegraphic, preventing a 5.

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

Completeness5/5

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

With no output schema, the description supplies the return shape (JSON with MP3 base64, voice, model, safety verdict), plus error behavior (422 on unsafe) and pricing. Nothing critical for correct invocation is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds value the schema lacks: it enumerates the actual lang values (en, ko, ja, zh, es, fr) where the schema only says 'default en', and restates the 500-char cap. That goes beyond the structured field.

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?

States a specific verb+resource ('spoken audio from short text') plus the concrete output format (MeloTTS MP3, 6 languages). An agent can distinguish this from ai_image and other siblings without opening any schema.

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

Usage Guidelines4/5

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

Gives clear when-to-use contexts (voice reply, narration, accessibility) and notes fixed built-in voices / no voice cloning in the same breath. It does not explicitly name an alternative tool or exclusion, which keeps it just below a 5.

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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