music
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.
- License 许可
- MIT
- 最近更新
- 2026-08-25
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- ★ 0
- Forks
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01 前言 Front Matter
- name
- music
- license
- MIT
- metadata
- { "openclaw": { "requires": { "env": [ "ELEVENLABS_API_KEY" ] }, "primaryEnv": "ELEVENLABS_API_KEY" } }
- description
- 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.
- compatibility
- Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY).
02 资源文件 2
- 参考文档references/api_reference.md4.9 KB
- 参考文档references/installation.md1.5 KB
03 SKILL.md 正文
ElevenLabs Music Generation
Generate music from text prompts - supports instrumental tracks, songs with lyrics, and fine-grained control via composition plans.
Setup: See Installation Guide. For JavaScript, use
@elevenlabs/*packages only.
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
)
with open("output.mp3", "wb") as f:
for chunk in audio:
f.write(chunk)
JavaScript
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,
});
audio.pipe(createWriteStream("output.mp3"));
cURL
curl -X POST "https://api.elevenlabs.io/v1/music" \
-H "xi-api-key: $ELEVENLABS_API_KEY" -H "Content-Type: application/json" \
-d '{"prompt": "A chill lo-fi beat", "music_length_ms": 30000}' --output output.mp3
Methods
| Method | Description |
|---|---|
music.compose |
Generate audio from a prompt or composition plan |
music.composition_plan.create |
Generate a structured plan for fine-grained control |
music.compose_detailed |
Generate audio + composition plan + metadata |
music.upload |
Upload an audio file for later inpainting workflows and optionally extract its composition plan |
See API Reference for full parameter details.
music.upload is available to enterprise clients with access to the inpainting feature.
Composition Plans
For granular control, generate a composition plan first, modify it, then compose:
plan = client.music.composition_plan.create(
prompt="An epic orchestral piece building to a climax",
music_length_ms=60000
)
# Inspect/modify styles and sections
print(plan.positiveGlobalStyles) # e.g. ["orchestral", "epic", "cinematic"]
audio = client.music.compose(
composition_plan=plan,
music_length_ms=60000
)
Content Restrictions
- Cannot reference specific artists, bands, or copyrighted lyrics
bad_prompterrors include aprompt_suggestionwith alternative phrasingbad_composition_planerrors include acomposition_plan_suggestion
Error Handling
try:
audio = client.music.compose(prompt="...", music_length_ms=30000)
except Exception as e:
print(f"API error: {e}")
Common errors: 401 (invalid key), 422 (invalid params), 429 (rate limit).
References
04 同仓库更多 Skills
syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.
pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
patent
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
notebooklm
Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.
litreview
Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed/OpenAlex (or Consensus) query.
grants
NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.