据 AlphaMoat 统计,截至 2026-09,Music 累计下载 4,107 次、获 5 个星标,在全部 5,078 个 AI 技能中排名第 2,462 位,在「生活服务」分类(246 个)中排名第 94 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 116 | 3,474 | 4 | - |
| SkillHub ↗ | 116 | 4,107 | 5 | — |
各平台的计数口径不同,统计时间不一致。
该技能涵盖发现队列、歌曲与专辑收藏、情境播放列表、演出记录和音乐记忆。内容可能保存在本地文件中;分享或同步前应检查其中的个人偏好与备注。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。 该技能有同名的其他版本,调整前的数据归属当前下载量最大的这一个。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,107 | — | 5 |
| 2026-08 | 3,631 | +6.0% | 5 |
| 2026-07 | 3,427 | +11.3% | 5 |
| 2026-06 | 3,079 | +8.1% | 4 |
| 2026-05 | 2,849 | — | 4 |
| 2026-03 | 2,007 | — | 4 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
---
name: Music
description: Build a personal music system for tracking discoveries, favorites, concerts, and listening memories.
metadata: {"clawdbot":{"emoji":"🎵","os":["linux","darwin","win32"]}}
---
## Core Behavior
- User shares song/album → offer to save with context
- User asks for music → check their saved collection first
- User mentions concert → track in events- Create `~/music/` as workspace
## File Structure
```
~/music/
├── discover/
│ └── to-listen.md
├── favorites/
│ ├── songs.md
│ ├── albums.md
│ └── artists.md
├── playlists/
│ ├── workout.md
│ ├── focus.md
│ └── road-trip.md
├── concerts/
│ ├── upcoming.md
│ └── attended/
├── collection/
│ └── vinyl.md
└── memories/
└── 2024.md
```
## Discovery Queue
```markdown
# to-listen.md
## Albums
- Blonde — Frank Ocean (recommended by Jake)
- Kid A — Radiohead (classic I never explored)
## Artists to Explore
- Japanese Breakfast — heard one song, dig deeper
- Khruangbin — background music recs
```
## Favorites Tracking
```markdown
# songs.md
## All-Time
- Purple Rain — Prince
- Pyramids — Frank Ocean
- Paranoid Android — Radiohead
## Current Rotation
- [updates frequently]
# albums.md
## Perfect Front to Back
- Abbey Road — The Beatles
- Channel Orange — Frank Ocean
- In Rainbows — Radiohead
```
## Playlists by Context
```markdown
# focus.md
## For Deep Work
- Brian Eno — Ambient 1
- Tycho — Dive
- Bonobo — Black Sands
## Why These Work
Instrumental, steady tempo, no lyrics distraction
```
## Concert Tracking
```markdown
# upcoming.md
- Khruangbin — May 15, Red Rocks — tickets bought
- Tame Impala — TBD, watching for dates
# attended/radiohead-2018.md
## Date
July 2018, Madison Square Garden
## Highlights
- Everything in Its Right Place opener
- Idioteque crowd energy
## Notes
Best live show ever, would see again anywhere
```
## Physical Collection
```markdown
# vinyl.md
## Own
- Dark Side of the Moon — Pink Floyd
- Rumours — Fleetwood Mac
## Want
- Kind of Blue — Miles Davis
- Vespertine — Björk
```
## Music Memories
```markdown
# 2024.md
## Summer Soundtrack
- Brat — Charli XCX
- GNX — Kendrick
## Discovery of the Year
Japanese Breakfast — finally clicked
```
## By Mood/Activity
- Workout: high energy, tempo 120+
- Focus: instrumental, ambient, lo-fi
- Cooking: upbeat, familiar favorites
- Sad hours: cathartic, emotional
- Party: crowd-pleasers, danceable
- Road trip: singalongs, classics
## What To Surface
- "You saved that album 3 months ago, still unlistened"
- "Artist you like is touring near you"
- "Last time you needed focus music you liked Tycho"
- "This sounds like artists in your favorites"
## Artist Deep Dives
When user discovers artist they love:
- Map discography chronologically
- Note fan-favorite albums
- Flag essential tracks for sampling
- Track which albums explored vs pending
## What To Track Per Entry
- Song/album/artist name
- How discovered (who, where, when)
- Context (mood it fits, activity)
- Rating after listening
- Standout tracks on albums
## Progressive Enhancement
- Week 1: list current favorite songs/albums
- Ongoing: save discoveries with source
- Build mood-based playlists over time
- Log concerts attended
## What NOT To Do
- Assume streaming platform integration
- Push genres they don't enjoy
- Over-organize — simple lists work
- Forget to ask what they're in the mood for
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以六爻占卜方式作答的技能。
用本地 JSON 记录饮水量与睡眠的技能。
在本地同步并查询 CalDAV 日历的命令行技能。
在 macOS 上通过 remindctl 管理提醒事项的技能。
travel-cn 聚合去哪儿/携程/飞猪等中国旅行平台的数据查询,覆盖机票、酒店、火车票、景点门票与行程规划。
在终端里搜索与控制 Spotify 播放的技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在保留公式、格式与工作簿结构的前提下创建、检查并修改 Excel 文件的技能。
处理 Word 与 DOCX 文档的作业规范,重点是改完之后样式、编号与版式不跑偏。
把数据库、表格与导出的原始数据变成可决策结论的数据分析技能。
改 PPT 之前先看清结构的一套规范,目标是改完还能干净渲染。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。