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Generate music

generate_music

Turn a text prompt into a music track by specifying genre, mood, instrumentation, and tempo.

Instructions

Generate a music track from a text prompt. Typically takes 1–5 minutes depending on track length. Tell the user that wait up front.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesGenre, mood, instrumentation, and tempo.

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. First observedv2.2.1

TDQS

A4/5.0
Behavior4/5

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

Annotations only cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false); the description adds the critical long-running latency trait and an explicit UX instruction about surfacing the wait. It does not clarify whether the call blocks or returns an async handle.

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?

Three short sentences, front-loaded with the core action, then the latency constraint, then the actionable instruction to the agent. No filler.

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?

Output schema exists so return values need no explanation, and the latency trait is disclosed. The main remaining gap is whether this is an async/task-based call that later surfaces via list_tool_executions, which matters given the sibling task-management 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?

There is a single required parameter with 100% schema coverage, and the schema description ('Genre, mood, instrumentation, and tempo') is actually richer than the description's generic 'text prompt'. Baseline 3 applies since the schema already does the work.

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?

States a specific verb (generate) and resource (music track) from a text prompt, which cleanly separates it from siblings like generate_sound_effect, text_to_speech, and generate_video_clip. An agent can identify the operation without opening the schema.

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 gives operational guidance (1-5 minute wait, tell the user up front) but no tool-selection guidance explaining when to prefer this over generate_sound_effect or other audio siblings. Usage is implied by the resource name rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.