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music_generation

Generate AI music from text prompts and lyrics. Create custom audio tracks by describing style, mood, or scenes and providing song lyrics for musical composition.

Instructions

Create a music generation task using AI models. Generate music from prompt and lyrics.

COST WARNING: This tool makes an API call to Minimax which may incur costs. Only use when explicitly requested by the user.

Args:
    prompt (str): Music creation inspiration describing style, mood, scene, etc.
        Example: "Pop music, sad, suitable for rainy nights". Character range: [10, 300]
    lyrics (str): Song lyrics for music generation.
        Use newline (\n) to separate each line of lyrics. Supports lyric structure tags [Intro][Verse][Chorus][Bridge][Outro] 
        to enhance musicality. Character range: [10, 600] (each Chinese character, punctuation, and letter counts as 1 character)
    stream (bool, optional): Whether to enable streaming mode. Defaults to False
    sample_rate (int, optional): Sample rate of generated music. Values: [16000, 24000, 32000, 44100]
    bitrate (int, optional): Bitrate of generated music. Values: [32000, 64000, 128000, 256000]
    format (str, optional): Format of generated music. Values: ["mp3", "wav", "pcm"]. Defaults to "mp3"
    output_directory (str, optional): Directory to save the generated music file
    
Note: Currently supports generating music up to 1 minute in length.

Returns:
    Text content with the path to the generated music file or generation status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
lyricsYes
sample_rateNo
bitrateNo
formatNomp3
output_directoryNo
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing cost implications, API provider (Minimax), length limitation ('Currently supports generating music up to 1 minute in length'), and output behavior ('Text content with the path to the generated music file or generation status'). It could improve by mentioning authentication needs or rate limits, but covers key behavioral aspects.

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 well-structured with clear sections (purpose, warning, parameters, notes, returns) and front-loaded information. Most sentences earn their place, though the parameter explanations are quite detailed, which is necessary given the lack of schema descriptions but slightly reduces conciseness.

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 complexity of a 6-parameter music generation tool with no annotations and no output schema, the description provides comprehensive context including purpose, usage guidelines, detailed parameter semantics, behavioral constraints, and return information. The main gap is the lack of output schema details, but the description compensates reasonably well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by providing detailed semantics for all 6 parameters. It explains each parameter's purpose, provides examples, character ranges, supported values, defaults, and usage notes (like lyric structure tags and character counting rules). This adds substantial value beyond the bare 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 clearly states the tool's purpose with specific verbs ('Create a music generation task', 'Generate music from prompt and lyrics') and identifies the resource (music). It distinguishes from siblings like text_to_audio or voice_clone by focusing specifically on music generation with AI models, not just audio conversion or voice manipulation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidelines with the 'COST WARNING' section specifying when to use ('Only use when explicitly requested by the user') and when not to use (avoid unnecessary API calls to Minimax due to costs). It also distinguishes from alternatives by noting it's specifically for music generation, not other audio or media tasks.

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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