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Generate music (Suno)

aetherwave_generate_music

Generate AI music tracks from a style or mood description. Supports instrumental, custom lyrics, and model version selection; returns two tracks per submission.

Instructions

Generates AI music via Suno. Returns two tracks per submission. Default model is V5.5 (newest, best quality). For instrumental output set instrumental: true. Music gen typically takes 30-90s - this tool polls with up to a 6-minute budget. Note: the title param is advisory for instrumentals - Suno often writes its own title from the prompt content for instrumental generations. Transient GENERATE_AUDIO_FAILED errors are common; retry once before degrading the model version.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesStyle/mood/topic description. E.g. 'Lo-fi ambient track, rain sounds, warm pads' or 'High-energy synthwave with driving bass'.
instrumentalNoIf true, no vocals. Default false.
modelNoSuno model version. Defaults to V5_5 (current best).
titleNoOptional title for the generated tracks.
lyricsNoCustom lyrics. If omitted, Suno will generate lyrics from the prompt (unless instrumental=true).
Behavior5/5

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

Discloses polling behavior, error handling (transient GENERATE_AUDIO_FAILED errors, retry advice), and title advisory for instrumentals. Adds value beyond annotations which only show basic read/destructive hints.

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?

Four sentences covering key points with no fluff. Front-loaded with primary action and important details.

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?

Handles all critical aspects: generation action, return count, timing, error handling, parameter nuances. No output schema exists, but description sufficiently sets expectations.

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?

Enhances schema descriptions by noting default model V5.5, instrumental suppresses vocals, and title behavior for instrumentals. Schema coverage is 100%, so description provides additional context.

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?

Description clearly states it generates AI music via Suno, returns two tracks, and defaults to V5.5. Differentiates from sibling tools like generate_image and generate_video by specifying music generation.

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?

Provides context for instrumental output, model selection, and timing (30-90s with a 6-minute budget). While it doesn't explicitly name alternatives, the sibling tool list makes it clear when to use this tool versus others.

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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