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suno_overpainting

Add AI-generated vocals to your instrumental audio. Upload a track, set the time range for vocals, and receive the completed song with singing voice.

Instructions

Add AI-generated vocals to uploaded instrumental audio.

Takes your uploaded instrumental track and adds AI-generated vocals
on top of it (overpainting = painting vocals over the music).

Use this when:
- You have an instrumental track and want to add vocals
- You want to give background music a singing voice
- You need to add vocal melody to existing music

Returns:
    Task ID and the audio with vocals added.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_idYesID of the uploaded audio to add vocals to. Must be uploaded via suno_upload_audio.
overpainting_startNoStart time in seconds for adding vocals. Default is 0.
overpainting_endNoEnd time in seconds for adding vocals. Must be less than total song duration.
modelNoModel version to use.chirp-v5-5
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 provided, so description must cover behavioral traits. Describes the action and return value but lacks details on permission requirements, rate limits, or potential side effects. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise and front-loaded with the main action. Includes helpful bullet points for usage scenarios. Could be slightly tighter, but generally well-structured.

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 tool with 5 parameters and an output schema, the description covers the core functionality, usage context, and return format. Missing some behavioral details, but overall complete enough for an AI agent to understand and invoke 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 provides 100% coverage with descriptions for each parameter. The description adds minimal extra context (e.g., metaphor of 'painting vocals'), but the schema already sufficiently defines each parameter. Baseline score of 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?

Clearly states the tool adds AI-generated vocals to an uploaded instrumental audio file. Explains the term 'overpainting' and distinguishes from other tools like suno_extract_vocals and suno_underpainting.

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?

Explicitly lists three use cases with 'Use this when:' bullet points. Does not explicitly state when not to use, but context is clear given sibling tools.

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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