An AI-powered music curation engine that analyzes NetEase Cloud Music habits to provide daily personalized recommendations with free Bilibili streaming links.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install music-recommender
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install music-recommender using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Music Recommender?
The Music Recommender is a specialized utility designed for Openclaw Skills that transforms your existing music library into a source for intelligent discovery. By analyzing the metadata of a NetEase Cloud Music playlist, the skill profiles your unique listening taste, including artist preferences, language distribution, and preferred musical eras. It goes beyond simple suggestions by actively searching for free-to-play versions of recommended tracks on Bilibili, ensuring you can enjoy new music without platform-specific membership barriers.
Built for high-utility automation, this skill maintains a persistent history of recommendations to ensure you never receive the same song twice. It is particularly effective for users who want a high-quality, daily music digest delivered directly to their preferred communication channels like Telegram or saved into personal databases like Notion.
Music Recommender Use Cases
- Generating a fresh daily playlist based on current NetEase Cloud Music favorites.
- Finding free streaming alternatives on Bilibili for songs discovered on other platforms.
- Automated musical taste profiling to identify favorite genres such as indie folk, dream pop, or 90s nostalgia.
- Maintaining a clean, non-repetitive log of new musical discoveries for long-term tracking.
How Music Recommender Works
- The agent identifies a NetEase Cloud Music playlist link and extracts the unique playlist ID.
- A specialized Python script fetches the full list of songs, artists, and album metadata from the NetEase API.
- The AI performs a multi-dimensional taste analysis, profiling the user based on top artists, language mix, genre tags, and emotional mood.
- Ten unique songs are selected that match the taste profile but do not exist in the original playlist or previous history.
- The skill queries the Bilibili API to find the most relevant, high-quality video or audio link for each recommendation.
- The final list is formatted for mobile-friendly viewing and the results are logged in a timestamped JSON file to prevent future duplicates.
Music Recommender Setup
To integrate this with your Openclaw Skills environment, ensure the workspace directory for history is prepared:
mkdir -p ~/.openclaw/workspace/music-history/
The skill requires Python 3 and access to the internal scripts fetch_playlist.py, search_bilibili.py, and history.py. No external API keys are required as it utilizes standard web headers for NetEase and Bilibili requests.
Music Recommender Data Schema & Taxonomy
The skill organizes its data within the local workspace to manage history and profile analysis efficiently.
| Location | Data Type | Purpose |
|---|---|---|
~/.openclaw/workspace/music-history/ |
JSON Files | Stores daily recommendation logs named by date (e.g., 2026-03-29.json) |
/tmp/playlist_<id>.json |
JSON Cache | Temporary storage of the analyzed NetEase playlist structure |
Each recommendation entry follows this schema:
name: The title of the song.artists: The performer(s) associated with the track.bvid: The Bilibili Video Identifier.url: The direct URL for playback.
Music Recommender Advanced Features
- Smart De-duplication: Automatically checks all previous history files to ensure every recommendation is unique.
- Multi-Platform Export: Supports optional hooks to write daily recommendations directly to a Notion Music Database or generate a standalone HTML dashboard.
- Language-Aware Filtering: Identifies and balances the ratio of Chinese, English, Japanese, and Korean songs based on user preference.
- Membership-Free Streaming: Exclusively targets Bilibili links to provide a free listening experience regardless of the user's music subscription status.
SKILL.md
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