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producer_extend_music

Extend existing audio from a specific timestamp with new lyrics, styles, or sections. Add verses, bridges, or outros to build longer songs piece by piece.

Instructions

Extend an existing song from a specific timestamp with new content.

This allows you to continue a previously generated song, adding new sections
like additional verses, a bridge, or an outro.

Use this when:
- A generated song is too short and you want to add more
- You want to add a bridge or outro to an existing song
- You're building a longer song piece by piece

Returns:
    Task ID and the extended audio information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoWhether to process the request asynchronously.
lyricNoLyrics for the extended section. Use section markers like [Verse], [Chorus], [Bridge], [Outro]. The extension will continue from where the original song left off.
modelNoModel version to use for the extension.FUZZ-2.0
styleNoMusic style for the extension. Leave empty to maintain the original style, or specify to change the style mid-song.
audio_idYesID of the audio to extend. This is the 'id' field from a previous generation result.
continue_atYesTimestamp in seconds where to start the extension. For example, 120.5 means continue from 2 minutes and 0.5 seconds into the song.
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 responsibility. It states the return value ('Task ID and the extended audio information') and the general nature of the operation, but does not disclose whether the original song is preserved, whether the extension is non-destructive, or any limitations like maximum extension length or rate limits. This leaves important behavioral details ambiguous.

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 structured with a one-sentence summary, a brief explanatory paragraph, a bulleted use-case list, and a returns section. It is slightly more verbose than necessary, but every section contributes value and it is front-loaded with the core purpose.

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 tool's complexity (7 parameters, output schema, many siblings), the description provides sufficient context: when to use, what it does, and what it returns. It does not elaborate on async behavior or edge cases, but the schema and output schema cover those details, making the description adequately complete.

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%, with each parameter already having a detailed description. The tool description adds a little context (e.g., 'verses, bridge, outro' mapping to the lyric parameter) but does not meaningfully enhance understanding beyond what the schema provides. Baseline 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?

The opening sentence, 'Extend an existing song from a specific timestamp with new content,' uses a specific verb ('extend') and resource ('existing song') with a precise condition (timestamp). It clearly distinguishes from sibling tools like generate_music or cover_music by focusing on continuation rather than creation or transformation.

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 includes a 'Use this when:' section listing three concrete scenarios (song too short, adding bridge/outro, building piece by piece). This gives clear context for when to select this tool, though it does not explicitly name alternatives or specify when not to use it.

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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