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suno_extract_vocals

Extract isolated vocals from AI-generated songs by removing instrumentals. Create acapella tracks, remixes, or voice personas with optional time range selection for specific segments.

Instructions

Extract the vocal track from a generated song (stem separation).

Isolates the vocals from a song, removing instrumental background.
Useful for remixing, creating acapella versions, or persona creation.

Use this when:
- You want an isolated vocal track
- You need vocals for a remix or mashup
- You want to create a persona from specific vocal segments

Returns:
    Task ID and extracted vocal audio information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_idYesThe song ID to extract vocals from.
vocal_startNoStart time in seconds for the vocal extraction range.
vocal_endNoEnd time in seconds for the vocal extraction range.
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?

With no annotations provided, the description carries the full burden. It successfully discloses the async pattern by noting it returns a 'Task ID,' which is critical behavioral context. However, it omits other important traits: processing time expectations, whether the operation is destructive, rate limits, or authentication requirements.

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 perfectly structured with four distinct sections: definition, explanation, usage conditions, and return value. Every sentence earns its place; the core action is front-loaded, and the bullet points enhance scannability without verbosity.

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?

Given the presence of an output schema, the description appropriately summarizes the return value (Task ID + audio info) without redundancy. It covers domain-specific use cases (acapella, remixing). Only minor gaps remain regarding error handling or performance characteristics that would be expected for an async audio processing tool with no annotations.

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 the baseline score applies. The description implies temporal range extraction through the 'persona from specific vocal segments' use case, which loosely maps to vocal_start/vocal_end parameters, but adds no explicit syntax or format guidance beyond the schema.

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 opens with a precise action (extract) + resource (vocal track) + scope (generated song), and the second sentence clarifies the mechanism (isolates vocals, removes instrumental). It clearly distinguishes from full stem separation (sibling suno_stems_music) by focusing specifically on vocals.

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 'Use this when:' section provides explicit bullet-point scenarios (isolated vocals, remix/mashup, persona creation) that clearly signal appropriate usage. It cross-references persona creation (linking to suno_create_persona). However, it lacks explicit 'when not to use' guidance or contrast with suno_stems_music for instrumental separation needs.

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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