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Agent Skill · 音频生成

musical-dna(音乐 DNA)

用于辅助音频、音乐、语音转写、语音合成或声音素材处理。它适合让 Agent 生成配乐说明、整理音频流程、调用语音工具或处理播客和视频配音素材。使用时需要确认输入音频来源、输出格式、时长和模型限制;涉及人声克隆、版权音乐或公开发布时,应先核对授权和合规边界。

musical-dna 是音频生成类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在音频生成类的 283 个 Skill 里排第 76。

总安装 6,868周安装 292GitHub Stars 67下载 2,406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
MIT

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:musical-dna(音乐 DNA)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/musical-dna
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill musical-dna
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill musical-dna

这个 Skill 是做什么的

音频生成类 Skill 处理配音、配乐和音频素材的生成与转换。

musical-dna 用于辅助音频、音乐和语音素材处理,适合让 Agent 生成配乐说明或整理音频流程。适用于音频生成类创作场景,需确认输入音频来源和输出格式限制。通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和维护状态。涉及人声克隆或版权音乐时应先核对授权和合规边界。

当前无原始 SKILL.md 内容摘录,建议进一步查阅项目文档了解详细功能。

来源仓库内路径:skills/musical-dna

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/jwynia/agent-skills --skill musical-dna;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

    它需要需要联网,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

musical-dna 怎么安装?

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

musical-dna 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。

musical-dna 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

musical-dna 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

musical-dna 用的人多吗?

公开数据是累计安装 6,868 次,近一周安装 292 次,下载 2,406 次,GitHub 67 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。

musical-dna 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理音频生成类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

音频生成类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
music-cog

音乐齿轮 · OpenClaw

121,1044需要联网MIT-0通过
elevenlabs-music

十一实验室音乐 · OpenClaw

108,6181接触敏感数据MIT-0通过
music-generation

音乐一代 · OpenClaw

100,1385需要联网MIT-0有提醒
ace-music

王牌音乐 · OpenClaw

95,8682接触敏感数据MIT-0有提醒
mcp-applemusic

MCP applemusic 音频 · OpenClaw

79,3893调用外部服务MIT-0有提醒
musical-dna

音乐 DNA · 本页

6,86867需要联网MIT通过

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

Musical DNA Analysis

Purpose

Extract descriptive musical characteristics from any artist or band without using their name, building a vocabulary of sonic qualities for AI music generation, music description, or creative recombination. Replace "sounds like [Artist]" with specific, technique-focused descriptions.

Core Principle

How, not who. Describe techniques, approaches, and sonic qualities rather than referencing artists. This enables:

  • Ethical AI music generation
  • Precise communication about sound
  • Creative recombination of elements
  • Genre-independent vocabulary

Quick Reference: Six Dimensions

DimensionWhat to Analyze
Rhythmic FoundationDrums, tempo, bass lines, time signatures
Harmonic ArchitectureChords, modes, progressions, melodies
Instrumental TechniquesPlaying styles, effects, timbres
Production AestheticsRecording feel, mix, spatial treatment
Genre FusionInfluence integration, innovation points
Energy ArchitectureSong structure, dynamics, emotional trajectory

Analysis Process

Step 1: Select Representative Tracks

Choose 3-5 tracks that capture:

  • Their most recognizable sound
  • Range across their catalog
  • Both typical and boundary-pushing examples

Step 2: Systematic Deconstruction

Work through each dimension, focusing on specific techniques and approaches.

Step 3: Extract Prompt-Ready Phrases

Convert observations into standalone descriptive phrases that work without artist context.


Dimension 1: Rhythmic Foundation

Drum Character

  • Kit composition: Acoustic, electronic, hybrid, sampled
  • Stick technique: Brushes, rods, mallets, standard sticks
  • Snare approach: Rim shots, ghost notes, cross-stick, tight vs. ringy
  • Kick pattern: Four-on-floor, syncopated, polyrhythmic, sparse
  • Hi-hat work: Open/closed patterns, 16th note rides, swung
  • Fill style: Busy, minimal, tom-heavy, snare rolls

Time & Tempo

  • Time signatures: 4/4, 3/4, 6/8, odd meters (5/4, 7/8)
  • Tempo range: Locked BPM or flexible? Fast, mid, slow?
  • Subdivision emphasis: 8ths, 16ths, triplets, swung
  • Polyrhythmic layering: Multiple meters happening simultaneously

Bass Line DNA

  • Technique: Fingered, picked, slapped, synth, upright
  • Role: Rhythmic anchor vs. melodic counterpoint
  • Range: Sub-bass heavy, mid-focused, full range
  • Kick relationship: Locked, complementary, independent

Example Phrases:

  • "Driving 8th-note hi-hat over syncopated kick"
  • "Slapped bass with muted ghost notes"
  • "Swung triplet feel at 95 BPM"

Dimension 2: Harmonic Architecture

Chord Progressions

  • Major/minor balance: Predominantly one or mixed?
  • Modal inflections: Dorian darkness, Mixolydian brightness
  • Chromatic movement: Smooth voice leading, sudden shifts
  • Chord density: Triads, 7ths, extended (9ths, 11ths, 13ths)
  • Harmonic rhythm: Slow changes (1/bar) or rapid (2+/bar)

Tonal Centers

  • Key preferences: Sharp keys, flat keys, open-string friendly
  • Modulation: None, gradual, sudden, frequent
  • Scale choices: Natural minor, harmonic minor, pentatonic, modes
  • Dissonance tolerance: Clean resolution, lingering tension

Melodic Contour

  • Range: Wide intervals or narrow
  • Movement: Stepwise, leaping, arpeggiated
  • Phrase length: Short punchy or long flowing
  • Repetition balance: Hooks vs. development

Example Phrases:

  • "Minor key with Dorian 6th inflection"
  • "Slow harmonic rhythm, one chord per 4 bars"
  • "Wide interval leaps in vocal melody"

Dimension 3: Instrumental Techniques

Guitar Approaches

  • Pickup selection: Bridge (bright), neck (warm), split
  • Tone shaping: Treble-forward, mid-scoop, bass-heavy
  • Technique: Fingerpicking, flatpicking, hybrid, percussive
  • Tuning: Standard, drop D, open tunings, baritone

Effects Chain

  • Distortion type: Overdrive, fuzz, high-gain, clean
  • Time-based: Reverb (room, hall, plate), delay (analog, digital, tape)
  • Modulation: Chorus, phaser, flanger, tremolo, vibrato
  • Pitch: Octave, harmonizer, whammy
  • Dynamics: Compression (heavy, light, none)

Other Instruments

  • Keys/synth: Analog warmth, digital precision, organ, piano
  • Percussion: Auxiliary (tambourine, shaker), world instruments
  • Brass/strings: Section vs. solo, dry vs. lush
  • Electronics: Samples, loops, glitches, synthesis

Example Phrases:

  • "Neck pickup through mild tube overdrive"
  • "Slap-back delay with plate reverb"
  • "Fingerpicked acoustic with percussive body hits"

Dimension 4: Production Aesthetics

Spatial Characteristics

  • Environment feel: Professional studio, live room, bedroom, outdoor
  • Reverb treatment: Dry, intimate, expansive, cavernous
  • Stereo field: Wide, narrow, mono-compatible
  • Depth staging: Everything forward, layered front-to-back

Mix Philosophy

  • Prominence hierarchy: Drums-first, vocal-forward, guitar-heavy
  • Frequency allocation: Each instrument's spectral home
  • Dynamic range: Compressed, dynamic, limiting
  • Clarity vs. saturation: Pristine separation vs. glued warmth

Sonic Texture

  • Signal path: Clean, saturated, distorted, degraded
  • High frequency: Bright, airy, rolled-off, harsh
  • Low end: Tight, boomy, sub-heavy, absent
  • Midrange: Scooped, present, honky, balanced

Example Phrases:

  • "Bedroom recording aesthetic with lo-fi saturation"
  • "Drum-forward mix with tight low end"
  • "Vintage tape warmth with rolled-off highs"

Dimension 5: Genre Fusion Analysis

Influence Mapping

  • Primary foundation: The dominant genre base (60%+)
  • Secondary elements: Strong secondary influence (20-30%)
  • Tertiary accents: Occasional flavor (10% or less)

Integration Methods

  • Temporal placement: Genre X in verses, genre Y in choruses
  • Instrumental assignment: Drums from A, guitars from B
  • Transition approach: Seamless blend vs. jarring contrast
  • Era mixing: Vintage techniques + modern production

Innovation Points

  • Boundary crossing: Where conventions are broken
  • Novel combinations: Unexpected genre marriages
  • Signature fusion: Their unique contribution

Example Phrases:

  • "Math rock precision over post-punk foundation"
  • "Hip-hop production sensibility applied to folk songwriting"
  • "Grunge dynamics with shoegaze texture"

Dimension 6: Energy Architecture

Song Structure

  • Intro character: Atmospheric, punchy, fade-in, cold start
  • Verse energy: Pulled back, driving, building
  • Chorus intensity: Lift, explosion, subtle shift
  • Bridge/breakdown: Contrast, climax, reflection
  • Outro approach: Fade, stop, resolve, evolve

Dynamic Range

  • Intensity curves: Gradual build, sudden shifts, flat line
  • Peak placement: Early, middle, late, multiple
  • Release patterns: Sudden drop, gradual decay

Emotional Trajectory

  • Mood arc: Single state, journey, oscillation
  • Tension cycles: Build-release frequency
  • Climax character: Cathartic, devastating, transcendent

Example Phrases:

  • "Slow build across 4 minutes to explosive final chorus"
  • "Sudden dynamic drops creating tension"
  • "Verse-chorus contrast via density rather than volume"

Documentation Template

One-Sentence DNA

[Rhythmic approach] + [harmonic character] + [instrumental signature] + [production aesthetic]

Example: "Syncopated post-punk drumming over minor modal progressions, angular clean guitar with chorus effect, dry room recording with bass-forward mix"

Detailed Breakdown

## Rhythmic Signature
- Time feel:
- Drum character:
- Bass approach:
- Syncopation style:

## Harmonic DNA
- Chord tendencies:
- Scale preferences:
- Progression patterns:

## Instrumental Character
- Guitar tone/technique:
- Effects signature:
- Other key instruments:

## Production Fingerprint
- Recording aesthetic:
- Mix characteristics:
- Sonic texture:

## Genre Fusion Map
- Primary foundation:
- Secondary elements:
- Innovation points:

## Energy Architecture
- Typical structure:
- Dynamic range:
- Build patterns:

Extractable Prompt Elements

List 5-10 standalone phrases usable in AI generation:

  • "..."
  • "..."

Ethical Guidelines

Do

  • Combine elements from multiple analyses
  • Focus on techniques and approaches
  • Build reusable vocabulary
  • Create novel fusions

Don't

  • Copy complete profiles directly
  • Replicate signature riffs/melodies
  • Use as "sounds like [Artist]" substitute
  • Claim to reproduce specific artists

Anti-Patterns

1. The Name Drop

Pattern: Using artist names as shorthand instead of technique descriptions. "Sounds like Radiohead" instead of describing the actual sonic qualities. Why it fails: Defeats the entire purpose. Artist names are black boxes that convey different things to different people and may produce copyright issues in AI generation. Fix: Never use artist names in final output. For every "sounds like X," unpack what that actually means in terms of rhythm, harmony, production, etc.

2. The Single Dimension

Pattern: Analyzing only one dimension (usually rhythm or production) while ignoring others. Producing incomplete profiles. Why it fails: Musical identity emerges from interaction of all dimensions. A rhythmic profile without harmonic context is useless for generation. Fix: Force yourself through all six dimensions. Even if an artist seems "about the guitar sound," their rhythmic choices matter.

3. The Genre Substitute

Pattern: Describing music by genre labels instead of techniques. "Post-punk" instead of describing what makes it post-punk. Why it fails: Genre labels are contested categories, not techniques. AI systems need concrete instructions, not genre negotiations. Fix: Treat genre labels as starting points requiring unpacking. What rhythmic, harmonic, and production choices define this genre for this artist?

4. The Representative Track Trap

Pattern: Analyzing one famous song and extrapolating to entire catalog. Missing range and evolution. Why it fails: Artists vary. Their most famous song may not be representative. Analysis from one track produces narrow profiles. Fix: Analyze 3-5 tracks from different periods and modes. Look for both constants and variations.

5. The Technical Overdose

Pattern: Including so much technical detail that prompts become unusable. Every possible parameter specified. Why it fails: AI generation systems can't process unlimited context. Overly detailed prompts get truncated or confuse the model. Fix: Distill to 5-10 essential phrases. Prioritize what makes this artist distinct rather than comprehensive.

Integration Points

Inbound:

  • From listening to music you want to analyze

Outbound:

  • To AI music generation prompts
  • To lyric-diagnostic for complete song analysis

Complementary:

  • lyric-diagnostic: Lyrical analysis (words)
  • This skill: Musical analysis (sounds)

适合场景

01

生成背景音乐

02

生成歌曲或旋律

03

视频和播客配乐

04

社媒内容音频素材

能力概览

能力 1

调用音乐生成模型

能力 2

支持文本到音乐或歌曲生成

能力 3

提供 CLI 示例和使用场景

能力 4

适合音频内容工作流

平台分布

Claude Code

26.63%
按下载量换算641

OpenCode

25.98%
按下载量换算625

Antigravity

19.59%
按下载量换算471

Codex

13.9%
按下载量换算334

Gemini CLI

8.77%
按下载量换算211

Cursor

3.18%
按下载量换算77

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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