alter123-zz/music-recommender
skills/music-recommender/SKILL.md
AI音乐推荐引擎。根据心情、场景和偏好推荐音乐，生成个性化歌单。Keywords: 音乐推荐, 歌单, playlist, music recommendation.
$ install --global
skillsauthnpx skillsauth add alter123-zz/RaccoonClaw music-recommenderInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Apr 16, 2026, 2:35 AM40.0s3 files scanned
SKILL.md
- name:
- music-recommender
- description:
- AI音乐推荐引擎。根据心情、场景和偏好推荐音乐，生成个性化歌单。Keywords: 音乐推荐, 歌单, playlist, music recommendation.
AI音乐推荐 — 根据心情和场景推荐音乐生成歌单
概述
根据心情和场景推荐音乐生成歌单。适用于工作学习背景音乐、运动健身配乐、情绪调节、探索新音乐风格等场景。
触发关键词: 音乐推荐, 歌单, playlist, music recommendation
前置依赖
pip install requests spotipy
核心能力
能力1：基于Spotify/Last.fm API的音乐数据获取
基于Spotify/Last.fm API的音乐数据获取
能力2：场景化推荐——工作/运动/睡前/通勤等场景歌单
场景化推荐——工作/运动/睡前/通勤等场景歌单
能力3：智能风格匹配——BPM/能量值/情绪标签多维推荐
智能风格匹配——BPM/能量值/情绪标签多维推荐
命令列表
| 命令 | 说明 | 用法 |
|------|------|------|
| recommend | 推荐音乐 | python3 scripts/music_recommender_tool.py recommend [参数] |
| playlist | 生成歌单 | python3 scripts/music_recommender_tool.py playlist [参数] |
| mood | 按心情推荐 | python3 scripts/music_recommender_tool.py mood [参数] |
使用流程
场景 1
推荐适合下午办公的轻音乐
执行：
python3 scripts/music_recommender_tool.py recommend --scene office --mood relaxed
场景 2
生成跑步健身歌单
执行：
python3 scripts/music_recommender_tool.py playlist --scene workout --bpm 140
场景 3
推荐让人心情愉悦的歌曲
执行：
python3 scripts/music_recommender_tool.py mood --feeling happy
输出格式
# 📊 AI音乐推荐报告
**生成时间**: YYYY-MM-DD HH:MM
## 核心发现
1. [关键发现1]
2. [关键发现2]
3. [关键发现3]
## 数据概览
| 指标 | 数值 | 趋势 | 评级 |
|------|------|------|------|
| 指标A | XXX | ↑ | ⭐⭐⭐⭐ |
| 指标B | YYY | → | ⭐⭐⭐ |
## 详细分析
[基于实际数据的多维度分析内容]
## 行动建议
| 优先级 | 建议 | 预期效果 |
|--------|------|----------|
| 🔴 高 | [具体建议] | [量化预期] |
| 🟡 中 | [具体建议] | [量化预期] |
| 🟢 低 | [具体建议] | [量化预期] |
参考资料
原有链接
- Spotify Web API，音乐数据和推荐算法
- 偏好推荐模式参考
- MusicBrainz API，开放音乐元数据库
GitHub
- GitHub: Python Spotify API客户端，5k+ stars
HackerNews
- HackerNews: 基于情绪的AI音乐推荐算法
- Reddit r/spotify: spotify社区AI相关讨论
微信公众号
- 微信公众号: AI音乐推荐——场景化歌单生成
小红书
- 小红书: AI帮你生成完美歌单——根据心情推荐
注意事项
- 所有分析基于脚本获取的实际数据，不编造数据
- 数据缺失字段标注"数据不可用"而非猜测
- 建议结合人工判断使用，AI分析仅供参考
- 首次使用请先安装Python依赖：
pip install requests spotipy
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