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mcp-agent-chatterbox

mcp-agent-chatterbox

by ChristofMilius
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

stop_speech

Stop currently playing audio to cut off a long utterance started with wait=false. Use it to halt ongoing speech output from the Chatterbox MCP server.

Instructions

Stop audio that is currently playing. Useful for cutting off a long utterance started with wait=false.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "stop_speech"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It conveys the core effect (stopping playing audio) and a usage trigger, but omits details such as whether it stops all playback or only the current utterance, and what happens when nothing is playing.

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 short sentences, front-loaded with the core action and followed by a relevant usage note. Every sentence earns its place with no wasted wording.

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?

Given the tool's simplicity (no parameters, output schema present), the description covers the essential purpose and one usage context. It falls short only by not distinguishing this tool from related siblings like tts_unload, which an agent may need to choose correctly.

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?

The tool has zero parameters, so there is no parameter semantics to explain. The empty input schema is self-explanatory, and the description appropriately does not add unnecessary parameter details.

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 a specific verb and resource: 'Stop audio that is currently playing.' This clearly identifies the operation, but it does not differentiate the tool from siblings such as tts_unload, which may also stop audio, so the sibling-routing aspect is missing.

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?

It provides a clear usage scenario: 'Useful for cutting off a long utterance started with wait=false.' However, it does not name alternative tools or state when not to use this tool, leaving the agent to infer the boundary with tts_unload.

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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