How do I install the Claude Music Enhance skill?

Run npx skillmds@latest add agricidaniel/claude-music-enhance in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Claude Music Enhance safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Claude Music Enhance?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Claude Music Enhance free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Claude Music Enhance?

Agrici Daniel (@agricidaniel) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Claude Music Enhance by agricidaniel

Name: Claude Music Enhance
Author: Agrici Daniel

Claude Music Enhance

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.

Agrici Daniel Updated Sep 17, 2026

File contents

claude-music-enhance — Audio Post-Processing

Default path: loudness normalization (recommended first)

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.

Escape hatch 1 — AI vocal denoise (only if audible artifacts)

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.

Escape hatch 2 — stem separation (only if you need surgical edits)

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.

Decision tree

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)

Format conversion

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.).

Scripts used here

scripts/music_export.sh — default loudnorm + format conversion path.
~/.claude/skills/claude-video/scripts/audio_enhance.py — AI denoise and stem separation (external skill; must be installed separately).

---name: claude-music-enhancedescription: 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.---# claude-music-enhance — Audio Post-Processing## Default path: loudness normalization (recommended first)Loudness-normalize to the platform target in one ffmpeg call. This is theright answer 90% of the time — the generated audio is already clean; it justneeds the level right.```bash# 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 andthe measure-then-apply two-pass recipe if you need manual control.## Escape hatch 1 — AI vocal denoise (only if audible artifacts)Use only when you hear artifacts in vocals (hissing, AI mush, robot tones).FFmpeg normalization won't help; you need DeepFilterNet3.```bashsource ~/.video-skill/bin/activatepython3 ~/.claude/skills/claude-video/scripts/audio_enhance.py denoise \ input.flac --output output_clean.flac```Requires `claude-video` skill + DeepFilterNet3 weights. <1 GB VRAM.## Escape hatch 2 — stem separation (only if you need surgical edits)Use only when you need to fix vocals/drums/bass/other separately, then remix.Not needed for normal enhancement.```bashsource ~/.video-skill/bin/activatepython3 ~/.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.## Decision tree```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)```## Format conversionFor platform-specific export (codec/bitrate/sample-rate), use`claude-music-export` — it wraps `music_export.sh` with the right flags pertarget (Spotify FLAC, YouTube MP3 320k, TikTok M4A 256k, etc.).## Scripts used here- `scripts/music_export.sh` — default loudnorm + format conversion path.- `~/.claude/skills/claude-video/scripts/audio_enhance.py` — AI denoise and stem separation (external skill; must be installed separately).

Frequently asked questions