End-to-end AI music production workflow for Suno: album concept design, lyric writing with prosody checks, style prompt engineering, audio mastering for streaming platforms, promo video generation, and coordinated release management with distribution asset preparation.
Provides information about the bitwize-music plugin, its version, and its creator. Use when the user asks about the plugin, its purpose, version, or capabilities.
Creates visual concepts for album artwork and generates AI art prompts. Use during planning for concept discussion, or after all tracks are Final for actual artwork generation.
Designs album concepts, tracklist architecture, and thematic planning through 7 structured phases. Use when planning a new album or reworking an existing album concept.
Shows a structured progress dashboard for an album with percentage complete per phase, blocking items, and status breakdown. Use for a quick visual overview of album progress.
Tracks and manages album ideas including brainstorming, planning, and status updates. Use when the user wants to add, review, or organize their album idea backlog.
Admin access level
Server config contains admin-level keywords
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Modifies files
Hook triggers on file write and edit operations
Modifies files
Hook triggers on file write and edit operations
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.
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 Suno V5 style prompt with genre tags and vocal direction
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.
/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.
This is where the engineering lives. The plugin is a case study in how far you can push Claude Code's plugin system.
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.
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 4.8 | 7 | Lyrics, Suno prompts, album concepts, legal/verification research — output quality defines the music |
| Reasoning | Sonnet 4.6 | 30 | Research coordination, pronunciation analysis, most workflows |
| Mechanical | Haiku 4.5 | 16 | Imports, validation, clipboard, help — speed over creativity |
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.
npx claudepluginhub bitwize-music-studio/claude-ai-music-skills --plugin bitwize-musicComprehensive Suno AI music prompt creation with automated artist research, structured prompts, genre-specific techniques, AI-slop avoidance, quality review, and Chrome automation for direct upload to suno.com
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AI audio engineering skills for mixing, mastering, effects, diagnostics, and session setup. Pairs with the Phantom MCP server for audio analysis.
Personal collection of agent skills using the open SKILL.md standard