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Music volume under narration

set_music_volume
Destructive

How loud the music plays under the narration, as a percent (0 silent to 100 full), the same slider as the Voiceover panel. It changes the mix only while narration plays; without narration the music plays at full level. Uses no credit; undoable. Keylight has no fade-in or fade-out control for the music volume.

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": {
      "listingId": "<listingId>",
      "volumePercent": "<volumePercent>"
    },
    "name": "set_music_volume"
  }
}

Input Schema

NameRequiredDescriptionDefault
listingIdYesListing id from list_listings.
volumePercentYesMusic level under the narration, 0 (silent) to 100 (full).

Output Schema

NameRequiredDescriptionDefault
statusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / volumePercent / description
      Added value: +"Music level under the narration, 0 (silent) to 100 (full)."
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses the conditional effect (only during narration), the no-narration fallback, that it uses no credit, that it is undoable, and that no fade controls exist. These are meaningful behavioral details for a mutating tool and do not contradict the annotations.

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 compact and front-loads the core purpose before adding conditional behavior, cost, undoability, and fade limitations. Every sentence contributes useful context without unnecessary repetition.

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?

For a simple two-parameter setter, the description covers scope, conditional behavior, cost, reversibility, and a relevant limitation. An output schema exists, so return values need not be described.

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 both parameters are already documented in the schema. The description reinforces the 0/100 volume scale and the narration-specific effect, but it adds little parameter-level meaning beyond the schema, so baseline 3 is appropriate.

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?

The description clearly states the specific setting: music volume under narration, expressed as a 0-100 percent slider. It distinguishes this from general music volume by repeatedly scoping the effect to narration playback, and it names the Voiceover panel equivalent.

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 gives a strong usage condition: the setting only affects the mix while narration plays, and without narration the music is full level. It does not explicitly name an alternative sibling such as set_music, but the scoped use case is clear enough for an agent to choose correctly.

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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