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Daily Song Recommender

by yjin94606-art · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install daily-song-recommender
Description
每日歌曲推荐技能。根据用户输入的音乐风格偏好,从多个平台综合推荐歌曲。当用户说"推荐首歌"、"今天听什么"、"给我放首歌"、"随机推荐"等时触发。用户提供喜欢的风格(流行/摇滚/爵士/古典/电子/民谣/说唱/日文/韩文/中文等),AI会综合各平台推荐合适的歌曲。
README (SKILL.md)

Daily Song Recommender 🎵

AI-powered music recommendation that searches the web for fresh recommendations!

How It Works

  1. User expresses music preference (or asks for random recommendation)
  2. AI searches the web for latest/trending songs matching that style
  3. AI presents 3-5 personalized recommendations with links and reasons

Trigger Examples

  • "recommend a song"
  • "what should I listen to today"
  • "play some rock music"
  • "I'm into jazz lately, any suggestions?"
  • "new indie rock recommendations"
  • "K-pop suggestions please"
  • "surprise me with something"
  • "what's trending in pop music"

Recommendation Process

Step 1: Understand Preference

Ask clarifying questions if needed:

  • "What genre are you in the mood for?"
  • "Any specific decade or style?"
  • "Do you prefer vocals or instrumental?"

Step 2: Web Search

Use web_search tool to find current recommendations:

Query: "best rock songs 2024 recommendations"
Query: "top jazz albums suggestions"
Query: "new K-pop songs trending"

Step 3: Present Recommendations

Format output like this:

🎵 Today's Recommendations

1. 【Song/Album Name】
   Artist: xxx
   Why it's great: xxx
   🔗 Listen: [link]

2. 【Song/Album Name】
   Artist: xxx
   Why it's great: xxx
   🔗 Listen: [link]

3. 【Song/Album Name】
   Artist: xxx
   Why it's great: xxx
   🔗 Listen: [link]

---
💡 Sources: [where recommendations came from]

Search Query Templates

Genre Search Query Examples
POP "top pop songs 2024 recommendations", "best new pop music"
Rock "best rock songs 2024", "new rock music recommendations"
Jazz "best jazz albums 2024", "new jazz music suggestions"
Classical "best classical music 2024", "contemporary classical recommendations"
Electronic "best electronic music 2024", "top EDM tracks"
Folk/Indie "best indie folk 2024", "new acoustic music"
Rap/Hip-Hop "best rap songs 2024", "top hip-hop releases"
J-Pop "best J-pop 2024", "trending Japanese music"
K-Pop "best K-pop 2024", "new Korean music releases"
Chinese "best Chinese songs 2024", "new Mandopop releases"
Vintage "best classic songs all time", "timeless music recommendations"
Chill "best chill music 2024", "relaxing ambient playlists"

Tips

  • Always search for current/recent recommendations when possible
  • Include release year in search for freshness
  • Check multiple sources for variety
  • Provide direct links to streaming platforms when found
  • Give 3-5 recommendations per session
  • Mix well-known artists with emerging ones for discovery
Usage Guidance
This skill appears coherent and low-risk: it only uses web searches to find songs and returns links. Before installing, confirm the platform's web_search tool respects privacy and rate limits, be cautious if it ever asks for streaming service credentials (this skill does not), and review any links it provides before clicking.
Capability Analysis
Type: OpenClaw Skill Name: daily-song-recommender Version: 1.1.0 The 'daily-song-recommender' skill is a straightforward music recommendation tool that uses the 'web_search' capability to find songs based on user preferences. The instructions in SKILL.md are well-defined, align perfectly with the stated purpose, and contain no evidence of malicious intent, data exfiltration, or harmful prompt injection.
Capability Assessment
Purpose & Capability
Name/description state it will search the web for music recommendations; the SKILL.md only instructs using a web_search tool and formatting results. No unrelated binaries, env vars, or services are requested.
Instruction Scope
Runtime instructions are limited to asking clarifying questions, running web_search queries, and returning formatted recommendations with links and sources. They do not direct reading files, accessing credentials, or contacting unexpected endpoints.
Install Mechanism
No install spec and no code files are present (instruction-only), so nothing is written to disk or fetched during install.
Credentials
The skill requires no environment variables, credentials, or config paths—proportional to a search-based recommender.
Persistence & Privilege
always is false and the skill is user-invocable; it does not request persistent system presence or permission to change other skills or system settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install daily-song-recommender
  3. After installation, invoke the skill by name or use /daily-song-recommender
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
**Major update: Now recommends fresh and trending songs by searching the web instead of a fixed built-in list.** - Replaces the static song library with AI-powered web search for up-to-date recommendations. - Supports all genres and provides 3-5 personalized song or album choices with links and reasons. - Recommendation process now includes clarifying questions to refine user preferences. - Outputs sources for transparency. - Added search query templates for each genre to improve search accuracy.
v1.0.1
- Updated SKILL.md to fully translate and modernize documentation to English - Improved and clarified genre support and trigger phrase instructions - Standardized output format for song recommendations - Cleaned up and consolidated genre keywords and built-in library descriptions - Added clearer instructions for advanced/specific genre recommendations
v1.0.0
Daily Song Recommender 1.0.0 - Initial release of daily-song-recommender. - Users receive daily song suggestions based on their preferred music genre. - Supports a wide variety of styles (pop, rock, jazz, classical, electronic, folk, rap, J-pop, K-pop, Chinese, vintage, chill). - Users trigger the skill with phrases like "推荐首歌", "今天听什么", or by specifying favorite genres. - Provides curated song details including title, artist, album, style, and a recommendation reason. - Includes an internal multi-genre song library and advanced recommendations for sub-genres and favorite artists.
Metadata
Slug daily-song-recommender
Version 1.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 3
Frequently Asked Questions

What is Daily Song Recommender?

每日歌曲推荐技能。根据用户输入的音乐风格偏好,从多个平台综合推荐歌曲。当用户说"推荐首歌"、"今天听什么"、"给我放首歌"、"随机推荐"等时触发。用户提供喜欢的风格(流行/摇滚/爵士/古典/电子/民谣/说唱/日文/韩文/中文等),AI会综合各平台推荐合适的歌曲。 It is an AI Agent Skill for Claude Code / OpenClaw, with 96 downloads so far.

How do I install Daily Song Recommender?

Run "/install daily-song-recommender" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Daily Song Recommender free?

Yes, Daily Song Recommender is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Daily Song Recommender support?

Daily Song Recommender is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Daily Song Recommender?

It is built and maintained by yjin94606-art (@yjin94606-art); the current version is v1.1.0.

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