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Fattly

by io.github.industriesfatty-spec
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fattly_generate_audio

Generates AI audio: a voiceover (mode=speech) from text, or music (mode=music) from a description. Returns a link to the mp3 file.

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": {
      "mode": "<mode>",
      "text": "<text>"
    },
    "name": "fattly_generate_audio"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeYesspeech = voiceover, music = music.
textYesText to read (speech) or a music description (music).
voiceNoVoiceover voice, e.g. Rachel, Aria, George (speech only).
secondsNoMusic length: 15, 30 or 60 (music only).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

The description discloses the output behavior by stating it returns a link to the mp3 file, which is useful beyond the annotations. It also clarifies that generation is conditional on mode, though it does not discuss processing time, costs, or side effects.

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 two concise sentences with no filler. It front-loads the core purpose and includes the important output detail without wasting 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?

For a tool with a complete input schema and annotations, the description is sufficient for an agent to understand the main generation modes and output format. It lacks only optional behavioral context like async behavior or credit usage, which are not essential for correct invocation.

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 description coverage is 100%, so the parameters are already well documented. The description mostly restates the schema's mode and text semantics without adding extra meaning, earning the baseline score.

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 identifies the tool as generating AI audio, either a voiceover from text or music from a description, and states the return value is an mp3 link. It is specific enough to distinguish from image/video generation siblings, though it does not explicitly name a sibling alternative.

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 mode parameter and phrasing 'from text' and 'from a description' imply when to use the tool for speech or music generation. However, there is no explicit guidance about when not to use it or how it compares to siblings such as fattly_clone_voice.

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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