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suno_samples_music

Add AI-generated musical samples to uploaded audio within a defined time range to enhance existing music with loops or motifs.

Instructions

Add AI-generated samples to uploaded audio.

Takes your uploaded audio and adds AI-generated musical samples
within the specified time range.

Use this when:
- You want to add sample loops or motifs to existing music
- You need to enhance a track with additional musical elements
- You want to add AI-generated samples to a specific section

Returns:
    Task ID and the audio with samples added.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_idYesID of the uploaded audio to add samples to. Must be uploaded via suno_upload_audio.
samples_startNoStart time in seconds for adding samples. Default is 0.
samples_endNoEnd time in seconds for adding samples. 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?

With no annotations provided, the description must disclose behavioral traits. It states the returns (Task ID and audio with samples added) and implies a non-destructive addition. However, it does not clarify whether the original audio is modified or preserved, nor does it mention authentication, rate limits, or async behavior beyond 'Task ID'.

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?

The description is fairly concise with a clear structure: purpose statement, explanation, usage list, and returns. However, the first two sentences are somewhat redundant ('Add AI-generated samples...' and 'Takes your uploaded audio and adds...'), which could be tightened.

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 output schema exists (has output schema: true), the description does not need to detail return values, but it does mention Task ID and audio. It covers the core functionality adequately for a tool with 5 parameters and 1 required field. Lacks some context about the model parameter's impact, but schema fills the gap.

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 schema already documents all parameters. The description adds no extra semantic information beyond reinforcing the purpose of samples_start and samples_end. Per guidelines, baseline is 3, and no additional value is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool adds AI-generated samples to uploaded audio, specifying the action and resource. It distinguishes from siblings like suno_all_stems_music and suno_concat_music by focusing on sample addition within a time range, though it could be more explicit about differentiation from similar tools like suno_overpainting.

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 three bullet-pointed use cases: adding sample loops, enhancing tracks, and adding samples to specific sections. This gives clear context for when to use the tool, but does not mention when not to use it or alternative tools, missing a bit of guidance.

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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