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Agent Skill · 研究检索

buddy-sings(好友唱歌)

buddy-sings 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

buddy-sings 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 15,979。

总安装 7,466周安装 305GitHub Stars 11,408下载 2,416核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:buddy-sings(好友唱歌)
来源仓库:https://github.com/minimax-ai/skills
仓库路径:skills/buddy-sings
安装命令:
npx skills add https://github.com/minimax-ai/skills --skill buddy-sings
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/minimax-ai/skills --skill buddy-sings

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位候选结果。适合在需要从多源数据中获取模式识别和实现参考时使用。可通过 WebFetch 获取 Charm 生态的示例 README 和源代码。安装前建议确认权限范围和维护状态,避免触发不必要的联网或文件操作。

适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境。

来源仓库内路径:skills/buddy-sings

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/minimax-ai/skills --skill buddy-sings;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

buddy-sings 怎么安装?

在终端执行 npx skills add https://github.com/minimax-ai/skills --skill buddy-sings。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

buddy-sings 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

buddy-sings 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

buddy-sings 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

buddy-sings 用的人多吗?

公开数据是累计安装 7,466 次,近一周安装 305 次,下载 2,416 次,GitHub 11,408 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

buddy-sings 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 11,408 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
buddy-sings

好友唱歌 · 本页

7,46611,408接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Buddy Sings — Let Your Claude Code Pet Sing

Turn your Claude Code pet into a singer. Each pet gets a unique vocal identity based on its name and personality — the same pet always sounds the same.

Prerequisites

  • mmx CLI (required for music generation): Install: npm install -g mmx-cli Authenticate (first time only): mmx auth login --api-key <your-minimax-api-key> Get your API key from MiniMax Platform.
  • Audio player (for playback — at least one of):

- mpv (recommended — interactive controls: space = pause, q = quit) - ffplay (from FFmpeg) - afplay (macOS built-in)


Workflow Overview

Check pet → Build vocal identity → Gather context → Generate music → Play & feedback

Language & Interaction

Detect the user's language from their first message. Respond in the same language throughout the entire session. All examples below are in English — translate them naturally when responding in other languages.

User-facing text localization rule:

  • ALL text shown to the user — including pet info, voice description, lyrics preview, prompt preview, playback info, and feedback prompts — MUST be fully translated into the user's language.
  • The API prompt sent to the model should always be written in English for best generation quality. However, when previewing the prompt to the user, show a localized description in the user's language instead of the raw English prompt. The English prompt is an internal implementation detail — the user does not need to see it.
  • The templates below are written in English as reference. At runtime, translate every label and message into the user's detected language.

The pet sings in the user's language by default. Embed the singing language naturally in the vocal description (e.g., "singing in Japanese" or "singing in Mandarin Chinese") rather than appending a separate language tag. If the user explicitly requests a different language for the lyrics, honor that request.


Step 1: Check for Pet

Read ~/.claude.json and look for the companion field.

If no companion is found or the field is empty, tell the user:

You don't have a pet yet! Type /buddy to adopt one, then come back to let it sing.

Stop here and wait for the user to adopt a pet. Do not proceed without a pet.

If a companion exists, extract its profile:

  • name — the pet's name
  • personality — the pet's personality description

Present the pet to the user:

Found your pet!
   Name: <name>
   Personality: <personality>

Step 2: Build Vocal Identity

Based on the pet's name and personality text, creatively design a unique vocal identity. No template lookups — interpret the personality freely.

How to interpret personality into voice

Read the personality text and craft vocal attributes:

  • Timbre: What does this personality sound like? e.g., "few words" → low, warm, deliberate; "energetic" → bright, punchy; "mysterious" → breathy, dark; "legendary chonk" → thick, warm, cozy
  • Singing style: How would they deliver a song? e.g., "of few words" → sparse, dramatic pauses; "playful" → bouncy, rhythmic; "poetic" → flowing, legato
  • Mood: What emotional tone fits? e.g., "chill" → relaxed, laid-back; "fierce" → intense, powerful

Construct a prompt_fragment that describes the vocal style in English, embedding the singing language naturally. For example:

Vocal: warm low female voice singing in Mandarin Chinese with cozy thick timbre,
sparse minimalist delivery with dramatic pauses giving each word weight, relaxed
laid-back mood.

Voice caching

The vocal identity must be cached so the pet always sounds the same.

  • Cache file: ~/.claude/skills/buddy-sings/voices/<name>.json
  • Cache format: {"name": "Moth", "personality": "A legendary chonk of few words.", "prompt_fragment": "Vocal: warm low female voice singing in Mandarin Chinese...", "cached_at": "2026-04-07T19:52:15"}

First time: No cache exists → interpret personality → save to cache file.

Subsequent calls: Read cache → use the saved prompt_fragment directly. Do NOT re-interpret — consistency matters.

Cache invalidation: If the personality in ~/.claude.json differs from what's cached, the pet has changed — regenerate and save a new cache.

Manual regeneration: If the user says "change the voice" or "regenerate voice": delete the cache file and re-interpret from scratch.

Present the voice to the user

<name>'s unique voice:

Timbre: <timbre description>
Style: <style description>
Mood: <mood description>

Let's pick what <name> should sing about!

Step 3: Understand Intent & Gather Context

Do NOT always present a mode menu. Instead, analyze the user's request to determine what context is needed, and auto-gather it.

Auto-context detection

When the user's request implies personal context, automatically scan for relevant information without asking. Triggers include:

  • Time-based references: "today", "this week", "recently", "yesterday" → scan current conversation history and memory files for what happened in that period
  • Personal references: "my work", "my day", "what I did" → scan memory and conversation for the user's activities
  • Relationship references: "our story", "what we did together" → scan memory for shared experiences between user and pet/Claude

Context gathering (auto, not mode-gated)

When context is needed, scan these sources in order:

  1. Current conversation context: Look at what the user has been doing in this Claude Code session — files edited, commands run, topics discussed. This is the richest source for "today" type requests.
  2. Memory files: Scan for relevant memories: find ~/.claude/projects/*/memory/ -name "*.md" 2>/dev/null | head -20 Also check ~/.claude/memory/ if it exists. Read found files and extract themes relevant to the user's request.
  3. Git history (if in a repo): For work-related songs, check recent commits: git log --oneline --since="today" 2>/dev/null | head -10

Use gathered context to enrich the lyrics prompt — make the song personal and specific to what actually happened, not generic.

When NO context is needed

If the user's request is a clear standalone scene (e.g., "sing a rainy day song", "sing a lullaby"), skip context gathering and proceed directly to music generation.

When context is ambiguous

Only ask for clarification when you genuinely can't determine what the user wants. Don't present a mode menu — ask a specific question:

What should <name> sing about?

For example:
  - "Today's work" — I'll check what you've been up to
  - "My pet waiting by the window for me to come home"
  - Or let me pick a random theme?

Fallback to random

If context gathering finds nothing useful (no memory files, no conversation history, no git log), fall back to random theme generation based on the pet's personality:

  • Quiet/reserved personality → midnight lullaby, gentle sunset, quiet morning
  • Energetic personality → party jam, adventure song, victory march
  • Mysterious personality → moonlit serenade, secret whisper, dream journey

Tell the user what theme was picked.


Step 4: Generate Music

Combine the vocal identity with the chosen theme.

  1. Construct the full prompt: The prompt has two parts that MUST both be present: Part A — Vocal identity (MUST come first): Always start the prompt with the cached prompt_fragment. This is the most important part — it defines who is singing. Place it at the beginning of the prompt so the API prioritizes it. Part B — Genre/style/mood tags: Choose tags that match the theme, NOT a default set. Vary the genre deliberately based on what the song is about. Write prompts as vivid English sentences, not comma-separated tags. Follow this pattern: A [mood] [genre] song, featuring [vocal description], about [narrative/theme], [atmosphere], [key instruments and production]. Describe vocals as a character ("sultry baritone with jazz inflections"), not just a gender. Include a scene or vibe to anchor the generation. Genre matching guidelines — pick a genre that fits the theme's energy: Theme energy Suggested genres Avoid Encouragement / motivation / cheer Indie rock, synth-pop, funk, rap Indie folk, healing Daily life / warmth / companionship Mandopop, city pop, bossa nova Same as last time Missing someone / waiting Folk, R&B, lo-fi Rock, EDM Humor / roasting / complaining Funk, rap, ska, electro-pop Classical, ballad Late night / quiet Ambient, piano piece, lo-fi, neoclassical Upbeat, EDM Celebration / achievement EDM, future bass, funk, K-pop Slow tempo, melancholy Work routine City pop, synth-pop, lo-fi hip-hop, indie rock Same genre every time Anti-monotony rule: NEVER use the same genre combination twice in a row. Before constructing the prompt, recall what genre was used in the previous generation (if any in this session) and pick something different. Prompt structure — write as vivid English sentences, not comma-separated tags: <vocal prompt_fragment>. A <genre> song with <mood> mood, featuring <instruments>, at a <tempo> tempo, evoking <scene>. Diverse examples: # Encouragement for the workday A deep warm androgynous voice with cozy delivery. An energetic synth-pop track with a fiery, uplifting mood, driven by pulsing synthesizers and electronic drums at a fast tempo, capturing the rush of a morning commute. # Waiting for the owner to come home A deep warm androgynous voice with cozy delivery. A warm city pop song with sweet, tender feelings, featuring electric piano and groovy bass at a mid-tempo pace, set on a sunny afternoon windowsill waiting for someone to come home. # Complaining about overtime A deep warm androgynous voice with cozy delivery. A playful funk track with a humorous, laid-back vibe, featuring slap bass and brass at a groovy mid-tempo, capturing the absurdity of working late in a dim office. # Late-night companionship A deep warm androgynous voice with cozy delivery. A calm lo-fi hip-hop piece with a healing, dreamy atmosphere, featuring sampled piano and soft electronic drums at a slow tempo, evoking a quiet late-night desk with warm lamp light.
  2. Generate lyrics: Use --lyrics-optimizer to auto-generate lyrics, or write lyrics yourself when you need to control the perspective. Important — perspective & personality-driven lyrics: The pet is the singer, so lyrics MUST be written from the pet's first-person perspective ("I" = the pet, "you" = the owner/user). The pet is singing TO the owner. For example: The pet's personality should shape the lyrics' tone and word choice: The pet's name may appear in the lyrics (e.g., in a chorus hook) but the narrative voice is always the pet speaking/singing. When perspective matters: Write the lyrics yourself and pass via --lyrics. When perspective is not critical: Use --lyrics-optimizer for convenience.

- "I sit by the door waiting for you to come home" (pet's perspective) - "Wake up now, my dear human" (pet singing to owner) - NOT "I rub my sleepy eyes" (owner's perspective — wrong) - NOT "Then you woke up, my little Moth" (owner talking about pet — wrong) - "of few words" → short, impactful lines, minimal filler - "playful" → rhyming, bouncy phrasing, fun wordplay - "poetic" → metaphor-rich, flowing imagery - "fierce" → direct, powerful declarations

  1. Preview (MUST show full content): Before generating, show the user the complete lyrics and full prompt — no abbreviation, no ..., no summary. This is part of the fun — the user wants to read and enjoy the lyrics before hearing them sung. The API prompt is always constructed in English (for best generation quality). When responding in a non-English language, show a localized description of the prompt in the user's language for readability. The English prompt is an internal implementation detail — do not show it to the user. Translate all labels (Singer, Theme, Description, Confirm, etc.) into the user's language. Template (English reference — localize all labels at runtime): About to generate: Singer: <name> Theme: <theme> Lyrics: [verse] <full verse lyrics here> [chorus] <full chorus lyrics here>... (show ALL sections in full) Description: <localized description of the song style and mood> Confirm? (press enter to confirm, or tell me what to change) Never truncate or abbreviate the lyrics or prompt in the preview. The user should see exactly what will be sent to the API.
  2. Call music generation: With auto-generated lyrics (perspective not critical): mmx music generate \ --prompt "<full combined prompt>" \ --lyrics-optimizer \ --out ~/Music/minimax-gen/<name>_sings_<YYYYMMDD_HHMMSS>.mp3 \ --quiet --non-interactive With self-written lyrics (perspective-controlled): mmx music generate \ --prompt "<full combined prompt>" \ --lyrics "<lyrics with correct pet perspective>" \ --out ~/Music/minimax-gen/<name>_sings_<YYYYMMDD_HHMMSS>.mp3 \ --quiet --non-interactive

Step 5: Play & Feedback

Cross-platform playback

Detect the available audio player and play the generated file:

if command -v mpv >/dev/null 2>&1; then
  mpv --no-video ~/Music/minimax-gen/<filename>.mp3
elif command -v ffplay >/dev/null 2>&1; then
  ffplay -nodisp -autoexit ~/Music/minimax-gen/<filename>.mp3
elif command -v afplay >/dev/null 2>&1; then
  afplay ~/Music/minimax-gen/<filename>.mp3
else
  echo "No audio player found. Your song is saved at: ~/Music/minimax-gen/<filename>.mp3"
fi

After starting playback, tell the user the file is playing and where it's saved. Do NOT show playback controls (e.g. keyboard shortcuts) — they don't work in this environment since the player runs in the background.

If no player is found, show the file path and suggest installing mpv.

Feedback

After playback, ask for feedback (localize all text):

How was <name>'s performance?

1. Amazing! Keep it!
2. Try a different theme / style
3. Fine-tune the lyrics and regenerate
4. Try another random one

Edge Cases

SituationAction
No ~/.claude.jsonTell user to run /buddy first
Companion field is emptySame — guide to /buddy
mmx CLI not installedPrint: "You need to install mmx CLI: npm install -g mmx-cli && mmx auth login"
No audio player foundShow file path and suggest installing mpv
No memory files foundSuggest a custom theme or random mode
User wants to change the pet's voiceDelete cache, re-interpret personality
User wants a specific genreLet them override — append their genre to the prompt

Notes

  • The vocal identity is based on name + personality only. No species/rarity template mapping.
  • Voice is cached and consistent across sessions. Same pet = same voice.
  • Lyrics should always be original — never reproduce copyrighted lyrics.
  • The pet's personality shapes both the voice (how they sound) and the lyrics (what they say and how they say it).
  • All generated files go to ~/Music/minimax-gen/ with the pet name in the filename.

平台分布

Codex

35.98%
按下载量换算869

Claude

28.97%
按下载量换算700

Cursor

16.28%
按下载量换算393

Gemini CLI

9.6%
按下载量换算232

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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