claude-music-analyze
Analyzes audio files for BPM, musical key, loudness (LUFS), duration, format, and quality metrics. Uses ffprobe for metadata and…
Post-processing for generated music. Default path is FFmpeg loudness normalization (fast, CPU-only). Escape hatches: AI vocal denoise for artifacts, stem separation for surgical edits. Both escape-hatch paths reuse tooling from the claude-video skill.
$ npx -y skills add AgriciDaniel/claude-music --skill claude-music-enhance --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/claude-music-enhanceContext preview
The summary Claude sees to decide when to auto-load this skill.
Post-processing for generated music. Default path is FFmpeg loudness normalization (fast, CPU-only). Escape hatches: AI vocal denoise for artifacts, stem separation for surgical edits. Both escape-hatch paths reuse tooling from the claude-video skill.
name: claude-music-enhance description: > Post-processing for generated music. Default path is FFmpeg loudness normalization (fast, CPU-only). Escape hatches: AI vocal denoise for artifacts, stem separation for surgical edits. Both escape-hatch paths reuse tooling from the claude-video skill. when_to_use: > Use when the user says enhance, normalize, denoise, master, polish, loudness, stem separation, split vocals, or wants to clean AI artifacts. allowed-tools: - Bash - Read
Loudness-normalize to the platform target in one ffmpeg call. This is the right answer 90% of the time — the generated audio is already clean; it just needs the level right.
# Two-pass loudnorm to -14 LUFS (Spotify/YouTube/Apple/TikTok all target this). bash ~/.claude/skills/claude-music/scripts/music_export.sh spotify input.flac output.flac
See `references/post-processing.md` for the full platform × LUFS table and the measure-then-apply two-pass recipe if you need manual control.
Use only when you hear artifacts in vocals (hissing, AI mush, robot tones). FFmpeg normalization won't help; you need DeepFilterNet3.
source ~/.video-skill/bin/activate python3 ~/.claude/skills/claude-video/scripts/audio_enhance.py denoise \ input.flac --output output_clean.flac
Requires `claude-video` skill + DeepFilterNet3 weights. <1 GB VRAM.
Use only when you need to fix vocals/drums/bass/other separately, then remix. Not needed for normal enhancement.
source ~/.video-skill/bin/activate python3 ~/.claude/skills/claude-video/scripts/audio_enhance.py separate \ input.flac --model htdemucs_ft --output-dir ./stems/
Produces `vocals.wav`, `drums.wav`, `bass.wav`, `other.wav`. ~7 GB VRAM.
Is the generated audio too quiet or too loud?
→ use the default path (loudnorm)
Do you hear specific vocal artifacts?
→ escape hatch 1 (denoise) THEN default path (loudnorm)
Do you need to fix one stem (e.g., reduce drums, retune vocal) before final mix?
→ escape hatch 2 (separate) → edit stem → remix → default path (loudnorm)For platform-specific export (codec/bitrate/sample-rate), use `claude-music-export` — it wraps `music_export.sh` with the right flags per target (Spotify FLAC, YouTube MP3 320k, TikTok M4A 256k, etc.).
stem separation (external skill; must be installed separately).
Make full songs on your own computer by describing them in plain words. claude-music turns Claude Code into a music studio, powered by ACE-Step 1.5. Type "make me a chill lo-fi beat" and get a finished track in about 15 seconds.
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Browses, searches, and manages generated music in ~/Music/claude-music-output/. Lists recent generations, searches by date,…