claude-ai-music-skills
Human + AI music production workflow for Suno - skills, templates, and tools
- 评测生成时间(北京时间)
- 本报告引擎
- v3.10.0
- 当前引擎
- v3.16.0
本报告与当前引擎使用不同规则;原分数不会自动更新,不同版本的分数不宜直接对比。
进入后确认来源与额度,提交才会创建任务。
综合采用结论
证据充分,整体质量与安全表现优秀
- 基础评测完成+25/25确定性评分与静态安全扫描已完成
- README 有效证据+22/258,938 个去重后的有效字符
- 独立证据来源+20/205 类非重复证据,重复文件不叠加
- 仓库元数据+10/10已取得仓库状态与采用数据
- 活跃记录+5/5已取得最近提交时间
- AI 复核+15/15已完成结构化 AI 证据复核
专辑制作流程交互
文档示例工作流展示用户与Claude之间的多轮请求-响应,以及Claude内部调度研究、歌词、音频处理等步骤,适合用序列图表示。
左右滑动查看完整图示
- • Example Workflow 章节:用户说'Let's make an album...',Claude创建结构并运行7阶段概念规划
- • Example Workflow 章节:用户说'Start the research',Claude并行调度法律、金融、安全研究员
- • Example Workflow 章节:用户说'Track sounds great, here are the stems',Claude导入stems并母带至-14 LUFS
- Install 章节:/plugin marketplace add ... 和 /plugin install ...
- Example Workflow 章节:展示从概念到发布的对话示例
- Architecture 章节:描述53个技能、80+ MCP工具、多模型编排
- Quality Gates 章节:列出歌词、音频等检查点
- Platform 段落:说明支持macOS、Linux、WSL2、Windows,并提及Python 3.11+
- 问题与用途描述
- 有效 README
- 可执行示例
- 输入、参数或工具说明
- 未发现已知高风险模式
- 缺少安装或接入步骤
- 安装命令依赖Claude Code插件系统,未提供手动安装或替代方案
- 配置步骤仅提及命令,未说明具体参数或选项
- 依赖Suno平台,未说明无Suno账号时的替代流程
- 未提供最小可运行示例或独立于Claude Code的复现步骤
使用Claude Code并订阅Max的用户、需要从概念到发布完整音乐制作流程的创作者、对AI音乐生成与多模型编排感兴趣的技术用户、需要歌词、音频母带、发布准备一体化工具的用户
不使用Claude Code或无法安装插件的用户、仅需简单音乐生成而不需要完整制作流程的用户、依赖免费或低配额API的用户(可能遇到速率限制)
也有自己的公开项目?先看完证据,再用当前规则生成独立报告。
评测我的项目 →静态扫描不是安全保证,生产接入前仍应人工复核权限和数据边界。
- 01补充安装或接入步骤
方法、证据与局限展开收起
GitHub Repository API
25 个文件 · 215,718 字符
v3.10.0 · AI 复核已启用(deepseek-chat)
- 静态评测不会安装或执行项目代码
- 安全扫描基于高信号文件与已知模式,不能替代人工审计
- 流行度只反映采用程度,不代表安全或工程质量
30 天热度趋势
README
Claude AI Music Skills
I love music but never learned an instrument. AI became the creative outlet that was always out of reach. This project started as a way to go deep on Claude Code plugin architecture, agentic workflows, multi-model orchestration, and MCP tooling. Music was the domain because it was personal.
What it actually does: a Claude Code plugin that turns a conversation into a full album production pipeline. You describe what you want to make, and it handles concept development, lyrics, Suno prompts (an AI music generation platform), audio mastering, and release prep — with quality gates and source verification at every stage.
Questions? See the FAQ.
[!NOTE] Active development happens on the
developbranch —mainonly receives tested, stable releases. If you run into issues, open an issue or submit a PR.
Example Workflow
You: "Let's make an album about the 2016 Bangladesh Bank heist"
Claude: Creates album structure, runs 7-phase concept planning
You: "Start the research"
Claude: Dispatches legal, financial, and security researchers in parallel
Gathers DOJ filings, SWIFT documentation, malware analysis
Cross-verifies sources, flags claims that need human review
You: "Sources look good. Let's write track 1"
Claude: Drafts lyrics, checks prosody and rhyme schemes
Scans for pronunciation risks, suggests phonetic fixes
Builds the Suno style prompt and generation settings (model, Variety, Max Mode)
You: "Track sounds great, here are the stems"
Claude: Imports stems from Suno, polishes per-stem
Masters to -14 LUFS for streaming
Generates promo video and social media copy
Concept to released album. You generate on Suno, everything else happens in the terminal.
Install
/plugin marketplace add bitwize-music-studio/claude-ai-music-skills
/plugin install bitwize-music@bitwize-music
Then run /bitwize-music:setup to detect your environment and install dependencies. Run /bitwize-music:configure to set your artist name and workspace paths.
Platform: macOS, Linux, WSL2, and native Windows are all fully supported. The full test suite runs on windows-latest in CI (plus dedicated Windows legs for the MCP boot check and MuseScore PDF export) — the MCP server, state cache, non-audio workflow, and the ffmpeg audio pipeline all run natively there. Promo video works on Windows too, though it's verified by hand rather than continuously guarded (its tests mock ffmpeg). Sheet music works natively too: MuseScore PDF export is CI-verified on windows-latest, and AnthemScore transcription runs against a licensed install (its free trial exposes no CLI on any OS, so that caveat isn't Windows-specific). Python 3.11+ for the MCP server and audio tools. See the compatibility matrix for the per-feature breakdown.
Architecture
This is where the engineering lives. The plugin is a case study in how far you can push Claude Code's plugin system.
Skill System (53 Skills)
Each skill is a self-contained markdown file with a YAML frontmatter that declares its model, description, and when it should activate. Skills range from simple clipboard operations to multi-step creative workflows. Claude routes to skills automatically based on context, or you invoke them directly with /bitwize-music:<name>.
The lyric-writer knows prosody rules, rhyme scheme analysis, and Suno's pronunciation quirks. The mastering-engineer knows loudness targets per platform and genre-specific EQ curves. The researcher coordinates parallel sub-agents across 10 domain specializations.
See docs/skills.md for the full reference.
Multi-Model Orchestration
Skills declare which Claude model they need. Creative work that directly impacts music quality runs on Opus. Coordination and reasoning tasks use Sonnet. Mechanical operations (imports, validation, clipboard) run on Haiku.
| Tier | model: | Skills | Rationale |
|---|---|---|---|
| Creative | opus | 7 | Lyrics, Suno prompts, album concepts, legal/verification research — output quality defines the music |
| Reasoning | sonnet | 30 | Research coordination, pronunciation analysis, most workflows |
| Mechanical | haiku | 16 | Imports, validation, clipboard, help — speed over creativity |
Skills declare the tier alias, not a pinned version, so each one tracks the current frontier model in its tier automatically — no per-skill edit when a new Claude generation ships.
This project pushes Claude Code hard — multi-agent research, real-time audio analysis, sub-agent orchestration across model tiers. It works best on the Max subscription. The standard Pro subscription will hit rate limits during multi-track sessions.
See reference/model-strategy.md for per-skill rationale.
MCP Server (80+ Tools)
A Python MCP server exposes 80+ tools for instant state queries, audio analysis, lyrics processing, and database operations. The server is the plugin's nervous system — skills call MCP tools instead of reading files directly, which keeps responses fast and state consistent.
Key tool categories:
- State management — album/track lookups, session context, cache rebuild
- Lyrics analysis — syllable counting, readability scoring, rhyme detection, section validation, cross-track repetition
- Audio processing — mastering, stem analysis, QC checks, promo video generation
- Database — tweet/promo content management via PostgreSQL
Research System
For documentary and true-story albums, the research system coordinates parallel investigation across 10 domain-specific sub-agents. A lead researcher dispatches to specialists (legal, financial, security, government, journalism, etc.), each trained on where to find primary sources in their domain. A verification agent cross-checks all claims before human review.
The full pipeline: gather sources, verify citations, require human sign-off, then — and only then — allow lyrics generation. Every claim in the music traces back to a captured, verified source.
Quality Gates
Nothing ships without passing gates:
- Lyrics: 13-point checklist (rhyme, prosody, pronunciation, POV consistency, factual accuracy)
- Pre-generation: Sources verified, explicit flags set, style prompt complete, artist names cleared
- Audio: 7-point QC (loudness, clipping, silence, phase, stereo width, frequency balance, dynamic range)
- Structure: Album directory validation, file location checks, content integrity
Genre Coverage
72 genre directories with production guides, mastering presets, artist deep-dives, and Suno-specific tips. From afrobeats to vaporwave, each genre includes subgenre breakdowns, lyric conventions, and reference artists.
CI/CD
6 GitHub Actions workflows: tests (4,412 across ubuntu/macOS/Windows, plus lint, security scanning with bandit + pip-audit, and static validation), real-service integration (Postgres, SeaweedFS/S3, MuseScore), nightly deep tests, auto-release from changelog, PR target enforcement, and version sync. Dependabot watches pip and Actions versions weekly.
Coverage is measured on all three OSes and gated on the combined total, not one platform's view. That matters because every sys.platform == "win32" branch is unreachable on Linux — measuring only there made the platform-specific code invisible to the gate, which is exactly where this project's real bugs have lived. The merge is asserted rather than assumed: a mis-specified path mapping makes coverage combine report the Linux-only number while looking like success, so the job fails unless a known win32-only line is genuinely covered.
Project Structure
skills/ 53 skill definitions (markdown + YAML frontmatter)
servers/ MCP server (Python, 80+ tools)
tools/ Audio mastering, promo videos, sheet music, cloud uploads
reference/ 46+ docs — Suno guides, mastering workflows, genre references
genres/ 72 genre directories with production guides
templates/ Album, track, artist, research templates
tests/ 4,412 tests across 14 categories
config/ Example config and setup docs
Detailed Documentation
| Topic | Location |
|---|---|
| All 53 skills | docs/skills.md |
| Configuration | docs/configuration.md |
| Troubleshooting | docs/troubleshooting.md |
| Changelog | CHANGELOG.md |
| Contributing | CONTRIBUTING.md |
| Model strategy | reference/model-strategy.md |
| Skill decision tree | reference/SKILL_INDEX.md |
| Suno best practices | reference/suno/best-practices.md |
| Suno model catalog | reference/suno/models.md |
| The story behind bitwize-music | bitwizemusic.com/behind-the-music |
Contributors
If you make something with this, I'd genuinely love to hear it — @bitwizemusic on X, join the Discord, or open a discussion.
License
CC0 — Public Domain. Do whatever you want with it.
Disclaimer
Artist and song references in the genre documentation are for educational and reference purposes only. This plugin does not encourage creating infringing content. Users are responsible for ensuring their generated content complies with applicable laws and platform terms of service.









