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Generate sound effect

generate_sound_effect

Synthesize a standalone audio effect from a description of the desired sound and timing. Returns toolExecutionId; use get_tool_execution to retrieve the generated audio file and download URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the sound effect.
durationSecondsNoRequested sound-effect playback duration in seconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError details when status is failed; otherwise null.
statusNoJob status: pending, running, succeeded, failed, or cancelled.
resultsNoGenerated results with download URLs when succeeded.
toolTypeNoTool name (e.g. GENERATE_IMAGE).
attemptIndexNoCurrent or latest attempt index.
toolExecutionIdYesTool execution id (vg_tool_...).
progressPercentageNoCompletion progress 0-100 (present after polling).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / durationSeconds / description
      Added value: +"Requested sound-effect playback duration in seconds."
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare the safety profile (not read-only, not idempotent, not destructive, closed-world). The description adds genuinely new behavioral context: this is an async job that returns a toolExecutionId and requires a separate get_tool_execution call to obtain the file and download URL. It does not state expected latency or failure modes, keeping it below 5.

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?

Two sentences, zero filler. The generative purpose is front-loaded and the retrieval instruction follows immediately after; every clause earns its place.

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 two-parameter async generation tool with an output schema, the description covers purpose and the post-call retrieval flow, which is the critical operational detail. The only gap is disambiguation from sibling generators, which matters given the large family of generate_* tools.

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, giving a baseline of 3. The phrase 'desired sound and timing' loosely maps to prompt and durationSeconds but adds no format, unit, or constraint detail beyond what the schema already provides (including the 30-second maximum).

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?

States a specific verb and resource: 'Synthesize a standalone audio effect from a description of the desired sound and timing.' The word 'standalone' implicitly contrasts with generate_music, but no sibling is named explicitly, so an agent must infer the boundary between this and generate_music or text_to_speech.

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 description routes the agent to the follow-up step ('use get_tool_execution to retrieve the generated audio file'), which is useful lifecycle guidance, but it offers no when-to-use vs when-not guidance relative to the many sibling generation tools (generate_music, text_to_speech, generate_avatar). Usage is implied rather than stated.

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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