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Music

ElevenLabsOfficialPublished by ElevenLabs

  • Skill
  • Tool integration
  • Automation and integrations
  • MIT
  • Medium risk

From the author

Generate music using ElevenLabs Music API. Use when creating instrumental tracks, songs with lyrics, background music, jingles, or any AI-generated music composition. Supports prompt-based generation, composition plans for granular control, and detailed output with metadata.
— the description by ElevenLabs

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides an interface to the ElevenLabs Music API, enabling the generation of instrumental tracks, songs with lyrics, and background music. It supports prompt-based generation, structured composition plans for granular control, and advanced features like inpainting, video-to-music conversion, and custom finetuning.

What it does

  • Generates music from text prompts or structured composition plans.
  • Converts video files into synchronized background music scores.
  • Supports inpainting to edit or extend existing audio tracks.
  • Enables training and management of custom music finetunes.
  • Provides streaming capabilities for audio generation.
  • Allows detailed output with metadata and word-level timestamps.

When to use it

  • When you need to generate original background music or songs for creative projects.
  • When you require precise control over musical structure, lyrics, or instrumentation.
  • When you need to score video content with AI-generated music.
  • When you want to edit or extend previously generated audio using inpainting.

Advantages

  • Offers granular control via composition plans for specific sections and styles.
  • Supports both simple prompt-based generation and complex multi-step workflows.
  • Provides tools for managing and reusing custom music finetunes.
  • Enables integration with video workflows for automated scoring.

Usage examples

“Generate a 30-second chill lo-fi hip hop beat.”
The agent uses the music.compose method to generate an MP3 file based on the provided prompt and duration.
“Create a background score for this video file.”
The agent uses the music.video_to_music method to analyze the video and generate a matching musical score.
“Create a composition plan for an orchestral piece.”
The agent generates a structured JSON plan that can be edited before final audio synthesis.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/elevenlabs/music/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip music.zip -d .agents/skills

Documentation by ElevenLabs

ElevenLabs Music Generation

Generate music from text prompts - supports instrumental tracks, songs with lyrics, and fine-grained control via composition plans.

Setup, before writing any code: if ELEVENLABS_API_KEY isn't set for this project, run npx -y @elevenlabs/cli@latest onboard init from the app's folder first and follow what it prints: it signs the user in and stores a key for the project, so nobody copies one by hand. Otherwise see the Installation Guide. For JavaScript, use @elevenlabs/* packages only.

All examples below use music_v2_5, the most advanced generation model. Pass music_v2 or music_v1 only when an older model is explicitly requested.

Quick Start

Python
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.music.compose(
    prompt="A chill lo-fi hip hop beat with jazzy piano chords",
    music_length_ms=30000,
    model_id="music_v2_5",
)

with open("output.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
TypeScript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createWriteStream } from "fs";

const client = new ElevenLabsClient();
const audio = await client.music.compose({
  prompt: "A chill lo-fi hip hop beat with jazzy piano chords",
  musicLengthMs: 30000,
  modelId: "music_v2_5",
});
audio.pipe(createWriteStream("output.mp3"));
CLI
elevenlabs music compose \
  --prompt "A chill lo-fi beat" \
  --music-length-ms 30000 \
  --model-id music_v2_5 \
  --output output.mp3

Methods

MethodDescription
music.composeGenerate audio from a prompt or composition plan
music.streamStream audio chunks as they are generated (paid plans)
music.composition_plan.createGenerate a structured plan for fine-grained control
music.compose_detailedGenerate audio + composition plan + metadata; pass store_for_inpainting=True to enable inpainting
music.compose_detailed_streamStream audio plus composition plan, metadata, and optional word timestamps as Server-Sent Events
music.video_to_musicGenerate background music from one or more uploaded video files
music.uploadUpload an audio file for later inpainting workflows, optionally extracting its composition plan or word-level timestamps
music.finetunes.listList accessible music finetunes
music.finetunes.createTrain a music finetune from uploaded audio
music.finetunes.getRetrieve finetune status and metadata
music.finetunes.updateUpdate finetune metadata or visibility
music.finetunes.deleteDelete a music finetune

See API Reference for full parameter details.

music.upload is available to enterprise clients with access to the inpainting feature.

Music Finetunes

Create a finetune from training audio with POST /v1/music/finetunes, then poll the get endpoint until its status is completed. Pass the returned id as finetune_id when composing music.

Use the list, update, and delete endpoints to manage accessible finetunes.

Video to Music

Generate background music from uploaded video clips via POST /v1/music/video-to-music (client.music.video_to_music). This is separate from prompt-based music.compose (POST /v1/music).

The API combines videos in order, accepts an optional natural-language description, and lets you steer style with up to 10 tags such as upbeat or cinematic. This endpoint still defaults to music_v1; pass model_id="music_v2_5" to use the most advanced model.

Three optional flags shape the result: use_audio_as_reference takes genre, BPM, instrumentation, and mood from the video's own audio, add_sfx adds sound effects that match the video, and separate_tracks returns a ZIP with the music and sound effects as separate files for mixing.

Python
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.music.video_to_music(
    videos=["trailer.mp4"],
    description="Build suspense, then resolve with a warm cinematic finish.",
    tags=["cinematic", "suspenseful", "uplifting"],
    model_id="music_v2_5",
)

with open("video-score.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
TypeScript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createReadStream, createWriteStream } from "fs";

const client = new ElevenLabsClient();

const audio = await client.music.videoToMusic({
  videos: [createReadStream("trailer.mp4")],
  description: "Build suspense, then resolve with a warm cinematic finish.",
  tags: ["cinematic", "suspenseful", "uplifting"],
  modelId: "music_v2_5",
});

audio.pipe(createWriteStream("video-score.mp3"));
CLI
elevenlabs music video_to_music \
  --videos trailer.mp4 \
  --description "Build suspense, then resolve with a warm cinematic finish." \
  --tags cinematic \
  --model-id music_v2_5 \
  --output video-score.mp3

The CLI currently accepts one --videos file and one --tags value per request; use the Python or TypeScript SDK to send multiple videos or tags.

Constraints from the current API schema:

  • Upload 1-10 video files per request

  • Keep total combined upload size at or below 200 MB

  • Keep total combined video duration at or below 600 seconds

  • Use description for high-level musical direction and tags for concise style cues

Composition Plans

music_v2_5 composition plans are an ordered list of chunks. Each chunk specifies its own text (section label, lyrics, inline cues), duration_ms, positive_styles, negative_styles, and context_adherence (low, medium, or high, default high). Up to 30 chunks per plan, each 3,000–120,000 ms, total length 3 s to 10 minutes. Each chunk's text supports up to 6,132 characters, with up to 30 lines of 200 characters each.

Generate a plan first, edit it, then compose:

plan = client.music.composition_plan.create(
    prompt="An epic orchestral piece building to a climax",
    music_length_ms=60000,
    model_id="music_v2_5",
)

# Edit chunks in place
plan["chunks"][0]["text"] = "[Intro]\nQuiet strings rising"

audio = client.music.compose(
    composition_plan=plan,
    model_id="music_v2_5",
)
const plan = await client.music.compositionPlan.create({
  prompt: "An epic orchestral piece building to a climax",
  musicLengthMs: 60000,
  modelId: "music_v2_5",
});

plan.chunks[0].text = "[Intro]\nQuiet strings rising";

const audio = await client.music.compose({
  compositionPlan: plan,
  modelId: "music_v2_5",
});

Or hand-build a plan to control lyrics and style per section:

composition_plan = {
    "chunks": [
        {
            "text": "[Verse]\nWalking down an empty street",
            "duration_ms": 15000,
            "positive_styles": ["pop", "upbeat", "female vocals", "acoustic guitar"],
            "negative_styles": ["dark", "slow"],
            "context_adherence": "high",
        },
        {
            "text": "[Chorus]\nThis is my moment",
            "duration_ms": 15000,
            "positive_styles": ["powerful vocals", "full band"],
            "negative_styles": [],
            "context_adherence": "high",
        },
    ]
}

audio = client.music.compose(composition_plan=composition_plan, model_id="music_v2_5")
const compositionPlan = {
  chunks: [
    {
      text: "[Verse]\nWalking down an empty street",
      durationMs: 15000,
      positiveStyles: ["pop", "upbeat", "female vocals", "acoustic guitar"],
      negativeStyles: ["dark", "slow"],
      contextAdherence: "high",
    },
    {
      text: "[Chorus]\nThis is my moment",
      durationMs: 15000,
      positiveStyles: ["powerful vocals", "full band"],
      negativeStyles: [],
      contextAdherence: "high",
    },
  ],
};

const audio = await client.music.compose({
  compositionPlan,
  modelId: "music_v2_5",
});

Put broader characteristics (genre, instrumentation, vocal style) in positive_styles, not in text. The first chunk's styles set the overall tone — include 6–7 styles there.

Output Formats

Use the output_format query parameter on compose, detailed compose, or stream requests to select the generated audio format. auto chooses a model-appropriate MP3 format; for music_v2 and music_v2_5, it selects mp3_48000_192. Higher-bitrate MP3 options include mp3_48000_240 and mp3_48000_320.

Streaming

For paid plans, stream audio chunks as they are generated instead of waiting for the full file:

from io import BytesIO

stream = client.music.stream(
    prompt="A driving synthwave track with arpeggiated leads",
    music_length_ms=30000,
    model_id="music_v2_5",
)

buffer = BytesIO()
for chunk in stream:
    if chunk:
        buffer.write(chunk)
const stream = await client.music.stream({
  prompt: "A driving synthwave track with arpeggiated leads",
  musicLengthMs: 30000,
  modelId: "music_v2_5",
});

const chunks: Buffer[] = [];
for await (const chunk of stream) {
  chunks.push(chunk);
}
Detailed streaming

Use detailed streaming when the application needs generated music metadata while audio is still arriving. POST /v1/music/detailed/stream accepts the same prompt or composition-plan body as detailed compose, streams text/event-stream, and can include word timestamps with with_timestamps.

elevenlabs music compose_detailed_stream \
  --prompt "A bright indie pop hook with warm guitars" \
  --music-length-ms 30000 \
  --model-id music_v2_5 \
  --with-timestamps true \
  --output-format auto

Inpainting

Inpainting edits or extends a stored song by mixing audio reference chunks (unchanged slices of a stored song) with new generation chunks in a single composition plan.

Step 1 — get a song_id, either by storing a fresh generation or uploading existing audio:

# Option A: keep a generation for later editing
result = client.music.compose_detailed(
    prompt="An upbeat pop song with verse and chorus",
    music_length_ms=60000,
    model_id="music_v2_5",
    store_for_inpainting=True,
)
song_id = result.song_id

# Option B: upload an existing track and extract its plan
uploaded = client.music.upload(
    file=open("my-song.mp3", "rb"),
    extract_composition_plan="music_v2_5",
)
song_id = uploaded.song_id
composition_plan = uploaded.composition_plan
import { createReadStream } from "fs";

// Option A: keep a generation for later editing
const result = await client.music.composeDetailed({
  prompt: "An upbeat pop song with verse and chorus",
  musicLengthMs: 60000,
  modelId: "music_v2_5",
  storeForInpainting: true,
});
let songId = result.songId;

// Option B: upload an existing track and extract its plan
const uploaded = await client.music.upload({
  file: createReadStream("my-song.mp3"),
  extractCompositionPlan: "music_v2_5",
});
songId = uploaded.songId;
const compositionPlan = uploaded.compositionPlan;

Step 2 — compose a plan that references the stored audio and regenerates the part you want to change:

plan = {
    "chunks": [
        {"song_id": song_id, "range": {"start_ms": 0, "end_ms": 30000}},
        {
            "text": "[Chorus]\nWe're rising up tonight",
            "duration_ms": 30000,
            "positive_styles": ["bigger drums", "layered vocals", "anthemic"],
            "negative_styles": ["sparse"],
            "context_adherence": "high",
        },
    ]
}

audio = client.music.compose(composition_plan=plan, model_id="music_v2_5")
const plan = {
  chunks: [
    { songId, range: { startMs: 0, endMs: 30000 } },
    {
      text: "[Chorus]\nWe're rising up tonight",
      durationMs: 30000,
      positiveStyles: ["bigger drums", "layered vocals", "anthemic"],
      negativeStyles: ["sparse"],
      contextAdherence: "high",
    },
  ],
};

const audio = await client.music.compose({
  compositionPlan: plan,
  modelId: "music_v2_5",
});

To match the feel of a stored slice without copying it, attach a conditioning_ref (up to 30,000 ms) plus a condition_strength of low, medium, high, or xhigh to a generation chunk. Conditioning placed on the first chunk influences every later chunk.

See API Reference for the full inpainting parameter list.

Content Restrictions

  • Cannot reference specific artists, bands, or copyrighted lyrics

  • bad_prompt errors include a prompt_suggestion with alternative phrasing

  • bad_composition_plan errors include a composition_plan_suggestion

Error Handling

try:
    audio = client.music.compose(prompt="...", music_length_ms=30000)
except Exception as e:
    print(f"API error: {e}")
try {
  const audio = await client.music.compose({
    prompt: "...",
    musicLengthMs: 30000,
  });
} catch (err) {
  console.error("API error:", err);
}

Common errors: 401 (invalid key), 422 (invalid params), 429 (rate limit).

References

Files

SKILL.md

ElevenLabs Music Generation

Generate music from text prompts - supports instrumental tracks, songs with lyrics, and fine-grained control via composition plans.

Setup, before writing any code: if ELEVENLABS_API_KEY isn't set for this project, run npx -y @elevenlabs/cli@latest onboard init from the app's folder first and follow what it prints: it signs the user in and stores a key for the project, so nobody copies one by hand. Otherwise see the Installation Guide. For JavaScript, use @elevenlabs/* packages only.

All examples below use music_v2_5, the most advanced generation model. Pass music_v2 or music_v1 only when an older model is explicitly requested.

Quick Start

Python
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.music.compose(
    prompt="A chill lo-fi hip hop beat with jazzy piano chords",
    music_length_ms=30000,
    model_id="music_v2_5",
)

with open("output.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
TypeScript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createWriteStream } from "fs";

const client = new ElevenLabsClient();
const audio = await client.music.compose({
  prompt: "A chill lo-fi hip hop beat with jazzy piano chords",
  musicLengthMs: 30000,
  modelId: "music_v2_5",
});
audio.pipe(createWriteStream("output.mp3"));
CLI
elevenlabs music compose \
  --prompt "A chill lo-fi beat" \
  --music-length-ms 30000 \
  --model-id music_v2_5 \
  --output output.mp3

Methods

MethodDescription
music.composeGenerate audio from a prompt or composition plan
music.streamStream audio chunks as they are generated (paid plans)
music.composition_plan.createGenerate a structured plan for fine-grained control
music.compose_detailedGenerate audio + composition plan + metadata; pass store_for_inpainting=True to enable inpainting
music.compose_detailed_streamStream audio plus composition plan, metadata, and optional word timestamps as Server-Sent Events
music.video_to_musicGenerate background music from one or more uploaded video files
music.uploadUpload an audio file for later inpainting workflows, optionally extracting its composition plan or word-level timestamps
music.finetunes.listList accessible music finetunes
music.finetunes.createTrain a music finetune from uploaded audio
music.finetunes.getRetrieve finetune status and metadata
music.finetunes.updateUpdate finetune metadata or visibility
music.finetunes.deleteDelete a music finetune

See API Reference for full parameter details.

music.upload is available to enterprise clients with access to the inpainting feature.

Music Finetunes

Create a finetune from training audio with POST /v1/music/finetunes, then poll the get endpoint until its status is completed. Pass the returned id as finetune_id when composing music.

Use the list, update, and delete endpoints to manage accessible finetunes.

Video to Music

Generate background music from uploaded video clips via POST /v1/music/video-to-music (client.music.video_to_music). This is separate from prompt-based music.compose (POST /v1/music).

The API combines videos in order, accepts an optional natural-language description, and lets you steer style with up to 10 tags such as upbeat or cinematic. This endpoint still defaults to music_v1; pass model_id="music_v2_5" to use the most advanced model.

Three optional flags shape the result: use_audio_as_reference takes genre, BPM, instrumentation, and mood from the video's own audio, add_sfx adds sound effects that match the video, and separate_tracks returns a ZIP with the music and sound effects as separate files for mixing.

Python
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.music.video_to_music(
    videos=["trailer.mp4"],
    description="Build suspense, then resolve with a warm cinematic finish.",
    tags=["cinematic", "suspenseful", "uplifting"],
    model_id="music_v2_5",
)

with open("video-score.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
TypeScript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createReadStream, createWriteStream } from "fs";

const client = new ElevenLabsClient();

const audio = await client.music.videoToMusic({
  videos: [createReadStream("trailer.mp4")],
  description: "Build suspense, then resolve with a warm cinematic finish.",
  tags: ["cinematic", "suspenseful", "uplifting"],
  modelId: "music_v2_5",
});

audio.pipe(createWriteStream("video-score.mp3"));
CLI
elevenlabs music video_to_music \
  --videos trailer.mp4 \
  --description "Build suspense, then resolve with a warm cinematic finish." \
  --tags cinematic \
  --model-id music_v2_5 \
  --output video-score.mp3

The CLI currently accepts one --videos file and one --tags value per request; use the Python or TypeScript SDK to send multiple videos or tags.

Constraints from the current API schema:

  • Upload 1-10 video files per request

  • Keep total combined upload size at or below 200 MB

  • Keep total combined video duration at or below 600 seconds

  • Use description for high-level musical direction and tags for concise style cues

Composition Plans

music_v2_5 composition plans are an ordered list of chunks. Each chunk specifies its own text (section label, lyrics, inline cues), duration_ms, positive_styles, negative_styles, and context_adherence (low, medium, or high, default high). Up to 30 chunks per plan, each 3,000–120,000 ms, total length 3 s to 10 minutes. Each chunk's text supports up to 6,132 characters, with up to 30 lines of 200 characters each.

Generate a plan first, edit it, then compose:

plan = client.music.composition_plan.create(
    prompt="An epic orchestral piece building to a climax",
    music_length_ms=60000,
    model_id="music_v2_5",
)

# Edit chunks in place
plan["chunks"][0]["text"] = "[Intro]\nQuiet strings rising"

audio = client.music.compose(
    composition_plan=plan,
    model_id="music_v2_5",
)
const plan = await client.music.compositionPlan.create({
  prompt: "An epic orchestral piece building to a climax",
  musicLengthMs: 60000,
  modelId: "music_v2_5",
});

plan.chunks[0].text = "[Intro]\nQuiet strings rising";

const audio = await client.music.compose({
  compositionPlan: plan,
  modelId: "music_v2_5",
});

Or hand-build a plan to control lyrics and style per section:

composition_plan = {
    "chunks": [
        {
            "text": "[Verse]\nWalking down an empty street",
            "duration_ms": 15000,
            "positive_styles": ["pop", "upbeat", "female vocals", "acoustic guitar"],
            "negative_styles": ["dark", "slow"],
            "context_adherence": "high",
        },
        {
            "text": "[Chorus]\nThis is my moment",
            "duration_ms": 15000,
            "positive_styles": ["powerful vocals", "full band"],
            "negative_styles": [],
            "context_adherence": "high",
        },
    ]
}

audio = client.music.compose(composition_plan=composition_plan, model_id="music_v2_5")
const compositionPlan = {
  chunks: [
    {
      text: "[Verse]\nWalking down an empty street",
      durationMs: 15000,
      positiveStyles: ["pop", "upbeat", "female vocals", "acoustic guitar"],
      negativeStyles: ["dark", "slow"],
      contextAdherence: "high",
    },
    {
      text: "[Chorus]\nThis is my moment",
      durationMs: 15000,
      positiveStyles: ["powerful vocals", "full band"],
      negativeStyles: [],
      contextAdherence: "high",
    },
  ],
};

const audio = await client.music.compose({
  compositionPlan,
  modelId: "music_v2_5",
});

Put broader characteristics (genre, instrumentation, vocal style) in positive_styles, not in text. The first chunk's styles set the overall tone — include 6–7 styles there.

Output Formats

Use the output_format query parameter on compose, detailed compose, or stream requests to select the generated audio format. auto chooses a model-appropriate MP3 format; for music_v2 and music_v2_5, it selects mp3_48000_192. Higher-bitrate MP3 options include mp3_48000_240 and mp3_48000_320.

Streaming

For paid plans, stream audio chunks as they are generated instead of waiting for the full file:

from io import BytesIO

stream = client.music.stream(
    prompt="A driving synthwave track with arpeggiated leads",
    music_length_ms=30000,
    model_id="music_v2_5",
)

buffer = BytesIO()
for chunk in stream:
    if chunk:
        buffer.write(chunk)
const stream = await client.music.stream({
  prompt: "A driving synthwave track with arpeggiated leads",
  musicLengthMs: 30000,
  modelId: "music_v2_5",
});

const chunks: Buffer[] = [];
for await (const chunk of stream) {
  chunks.push(chunk);
}
Detailed streaming

Use detailed streaming when the application needs generated music metadata while audio is still arriving. POST /v1/music/detailed/stream accepts the same prompt or composition-plan body as detailed compose, streams text/event-stream, and can include word timestamps with with_timestamps.

elevenlabs music compose_detailed_stream \
  --prompt "A bright indie pop hook with warm guitars" \
  --music-length-ms 30000 \
  --model-id music_v2_5 \
  --with-timestamps true \
  --output-format auto

Inpainting

Inpainting edits or extends a stored song by mixing audio reference chunks (unchanged slices of a stored song) with new generation chunks in a single composition plan.

Step 1 — get a song_id, either by storing a fresh generation or uploading existing audio:

# Option A: keep a generation for later editing
result = client.music.compose_detailed(
    prompt="An upbeat pop song with verse and chorus",
    music_length_ms=60000,
    model_id="music_v2_5",
    store_for_inpainting=True,
)
song_id = result.song_id

# Option B: upload an existing track and extract its plan
uploaded = client.music.upload(
    file=open("my-song.mp3", "rb"),
    extract_composition_plan="music_v2_5",
)
song_id = uploaded.song_id
composition_plan = uploaded.composition_plan
import { createReadStream } from "fs";

// Option A: keep a generation for later editing
const result = await client.music.composeDetailed({
  prompt: "An upbeat pop song with verse and chorus",
  musicLengthMs: 60000,
  modelId: "music_v2_5",
  storeForInpainting: true,
});
let songId = result.songId;

// Option B: upload an existing track and extract its plan
const uploaded = await client.music.upload({
  file: createReadStream("my-song.mp3"),
  extractCompositionPlan: "music_v2_5",
});
songId = uploaded.songId;
const compositionPlan = uploaded.compositionPlan;

Step 2 — compose a plan that references the stored audio and regenerates the part you want to change:

plan = {
    "chunks": [
        {"song_id": song_id, "range": {"start_ms": 0, "end_ms": 30000}},
        {
            "text": "[Chorus]\nWe're rising up tonight",
            "duration_ms": 30000,
            "positive_styles": ["bigger drums", "layered vocals", "anthemic"],
            "negative_styles": ["sparse"],
            "context_adherence": "high",
        },
    ]
}

audio = client.music.compose(composition_plan=plan, model_id="music_v2_5")
const plan = {
  chunks: [
    { songId, range: { startMs: 0, endMs: 30000 } },
    {
      text: "[Chorus]\nWe're rising up tonight",
      durationMs: 30000,
      positiveStyles: ["bigger drums", "layered vocals", "anthemic"],
      negativeStyles: ["sparse"],
      contextAdherence: "high",
    },
  ],
};

const audio = await client.music.compose({
  compositionPlan: plan,
  modelId: "music_v2_5",
});

To match the feel of a stored slice without copying it, attach a conditioning_ref (up to 30,000 ms) plus a condition_strength of low, medium, high, or xhigh to a generation chunk. Conditioning placed on the first chunk influences every later chunk.

See API Reference for the full inpainting parameter list.

Content Restrictions

  • Cannot reference specific artists, bands, or copyrighted lyrics

  • bad_prompt errors include a prompt_suggestion with alternative phrasing

  • bad_composition_plan errors include a composition_plan_suggestion

Error Handling

try:
    audio = client.music.compose(prompt="...", music_length_ms=30000)
except Exception as e:
    print(f"API error: {e}")
try {
  const audio = await client.music.compose({
    prompt: "...",
    musicLengthMs: 30000,
  });
} catch (err) {
  console.error("API error:", err);
}

Common errors: 401 (invalid key), 422 (invalid params), 429 (rate limit).

References

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python, Needs Node.js

The author says: Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY).

Security

What our scanner noticed· Medium risk

  • Instructions that use the network
  • Downloads piped into a shell

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
ElevenLabs
Publisher
ElevenLabs (Official)
Source
elevenlabs/skills · music · commit 9763c39
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by ElevenLabs or ElevenLabs.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download music.zip