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suno_upload_cover

Generate an AI cover of your uploaded audio by setting a target style and model version.

Instructions

Create an AI cover of an uploaded audio (your own music).

Similar to suno_cover_music but works with audio you uploaded via
suno_upload_audio. Re-arranges your music in a different style.

Use this when:
- You uploaded your own music and want a cover in a different style
- You want to hear your song re-interpreted by AI

Returns:
    Task ID and the cover audio information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_idYesID of the uploaded audio to create a cover of. Must be an audio uploaded via suno_upload_audio.
styleNoTarget music style for the cover.
modelNoModel version to use.chirp-v5-5
audio_weightNoAdvanced parameter for cover operations. Controls how much the original audio influences the cover generation.
callback_urlNoWebhook callback URL for asynchronous notifications.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool re-arranges music and returns a task ID and audio info, but does not mention safety, auth, rate limits, or side effects. Adequate but not rich.

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 very concise: four sentences and bullet points. It starts with the main action, includes usage cases, and mentions return value. No unnecessary words.

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?

Given the tool's complexity (5 params, output schema exists), the description is complete. It distinguishes from sibling, explains prerequisites, and states return type. No gaps for an agent to use it correctly.

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 coverage is 100%, baseline is 3. The description adds minimal extra meaning beyond the schema descriptions, such as noting that 'audio_id' must be from 'suno_upload_audio'. This is useful but does not significantly enhance parameter understanding.

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 tool creates an AI cover of an uploaded audio. It explicitly differentiates from sibling 'suno_cover_music' by specifying it works with audio uploaded via 'suno_upload_audio', making the purpose distinct.

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?

The description provides explicit usage scenarios (uploaded music, different style, re-interpretation) and compares to a sibling. It lacks a direct 'when not to use' statement, but the provided cases are clear enough.

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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