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Troubleshoot audio

troubleshoot_audio

Diagnose why the avatar's mouth is not moving with ChatGPT's voice, and fix the audio source.

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": "troubleshoot_audio"
  }
}

Input Schema

NameRequiredDescriptionDefault
symptomNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the agent knows this tool can write but is not destructive. The description nonetheless never says what 'fix the audio source' actually changes, whether the change is reversible, or what happens on failure, which is important for a repair tool that mutates configuration.

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?

One compact sentence that leads with the diagnostic action and the observable symptom. It is efficient, though it could carry one more clause about the fix without becoming bloated.

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?

With no output schema and an undocumented parameter, the description would need to explain the diagnostic result and the fix side effects. It instead stops at a one-line purpose statement, leaving an agent unsure what to expect back or what state changes after invocation.

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

Parameters2/5

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

The single symptom parameter has 0% schema description coverage, and the description never mentions it, so the description contributes nothing here. The enum values are fairly self-explanatory, but which symptom maps to which fix behavior, and how omitting the optional parameter is handled, is left undocumented.

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 names a specific verb plus resource: it diagnoses avatar lip-sync failure with ChatGPT's voice and fixes the audio source. That is materially clearer than the bare name, though it does not distinguish itself from adjacent avatar-player tools such as player_status or link_player.

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 trigger condition, namely the mouth not moving with ChatGPT's voice, is stated implicitly, which is enough to infer when to reach for it. However, there is no guidance on ordering relative to siblings (for example, checking player_status first) and no exclusions or prerequisites.

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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