Strudel Music

Rendering MUST run as a sub-agent or background process, never inline in your main session.

The offline renderer (chunked-render.mjs / offline-render-v2.mjs) runs a tight audio-processing loop that blocks the Node.js event loop. If you run it in your main OpenClaw session, it will kill the gateway after ~30 seconds (the heartbeat timeout).

✅ Correct: spawn a sub-agent or use background exec
❌ Wrong:   run the renderer inline in your main conversation

Always do this:

# Background exec with timeout
exec background:true timeout:120 command:"node src/runtime/chunked-render.mjs src/compositions/my-track.js output/my-track.wav 20"

Or spawn a sub-agent:

sessions_spawn task:"Render strudel-music composition: node src/runtime/chunked-render.mjs ..."

This is the #1 way to break things. Don't skip this.

Quick Start

# 1. Setup
cd ~/.openclaw/workspace/strudel-music
npm run setup              # installs deps + downloads samples (~11MB)

# 2. Verify
npm test                   # 12-point smoke test

# 3. Render
node src/runtime/chunked-render.mjs assets/compositions/fog-and-starlight.js output/fog.wav 16
ffmpeg -i output/fog.wav -codec:a libmp3lame -b:a 192k output/fog.mp3

Commands

Composition Workflow

1. Parse prompt → select mood, key, tempo, instruments (see references/mood-parameters.md)
2. Write a .js composition using Strudel pattern syntax
3. Render (in background!):

   node src/runtime/chunked-render.mjs <file> <output.wav> <cycles> [chunkSize]
   

4. Convert to MP3:

   ffmpeg -i output.wav -codec:a libmp3lame -b:a 192k output.mp3
   

5. Post the MP3 as attachment or stream to Discord VC

Discord VC Streaming

node src/runtime/offline-render-v2.mjs assets/compositions/combat-assault.js /tmp/track.wav 12 140
ffmpeg -i /tmp/track.wav -ar 48000 -ac 2 /tmp/track-48k.wav -y
node scripts/vc-play.mjs /tmp/track-48k.wav

WSL2 users: enable mirrored networking (networkingMode=mirrored in .wslconfig) or VC streaming will fail silently (NAT breaks Discord's UDP voice protocol).

Sample Management

Directory Layout

Samples live in samples/. Any directory of WAV files is auto-discovered.

samples/
├── strudel.json          ← sample map (pitch info, paths)
├── kick/
│   └── kick.wav
├── hat/
│   └── hat.wav
├── bass_Cs1/
│   └── bass_Cs1.wav      ← pitched sample (root: C#1)
├── synth_lead/
│   └── synth_lead.wav     ← pitched sample (root: C#3, declared in strudel.json)
└── bloom_kick/
    └── bloom_kick.wav     ← from audio deconstruction

strudel.json Format

Maps sample names to files with optional root note declarations. The renderer uses this as the authoritative source for pitch detection.

{
  "_base": "./",
  "kick": { "0": "kick/kick.wav" },
  "bass_Cs1": { "cs1": "bass_Cs1/bass_Cs1.wav" },
  "synth_lead": { "cs3": "synth_lead/synth_lead.wav" }
}

• Keys with note suffixes (_Cs1, _D2) declare the root pitch
• Unpitched samples use "0" as the key
• Always declare root notes for pitched samples — without it, the renderer defaults to C4, causing wrong transpositions (see docs/KNOWN-PITFALLS.md)

Managing Packs

bash scripts/samples-manage.sh list              # show installed packs
bash scripts/samples-manage.sh add <url>          # download from URL
bash scripts/samples-manage.sh add ~/my-samples/  # add local directory

Ships with dirt-samples (153 WAVs, CC-licensed). Security: downloads enforce size limits (STRUDEL_MAX_DOWNLOAD_MB, default 10GB), MIME validation, optional host allowlist (STRUDEL_ALLOWED_HOSTS).

Composition Guide

Pattern Basics

CC0 / Free packs (just download and drop in samples/):

• Dirt-Samples — 800+ samples (full pack, we ship a subset)
• Signature Sounds – Homemade Drum Kit (CC0) — 150+ one-shots
• Looping – Synth Pack 01 (CC0) — synth one-shots + loops
• artgamesound.com — CC0 searchable aggregator

Your own packs: Export from any DAW (Ableton, FL Studio, M8 tracker, etc.) as WAV directories. Strudel doesn't care where they came from — it's just WAV files in folders.

Named banks (Strudel built-in, requires CDN access):

sound("bd sd cp hh").bank("RolandTR909")
sound("bd sd hh oh").bank("LinnDrum")

WSL2 Note

If running on WSL2 and streaming to Discord VC, enable mirrored networking:

# %USERPROFILE%\.wslconfig
[wsl2]
networkingMode=mirrored

Then wsl --shutdown and relaunch. Without this, WSL2's NAT breaks Discord's UDP voice protocol — the bot joins the channel but no audio flows because IP discovery packets can't traverse the NAT return path. Mirrored mode eliminates the NAT by putting WSL2 directly on the host's network stack.

This only affects VC streaming. Offline rendering and file posting work in any networking mode.

Platform Requirements

Two tiers, depending on what you need:

Compose & Render (JS-only)

• Node.js 18+ (22+ recommended for stable OfflineAudioContext)
• ffmpeg (MP3/Opus conversion)
• Works everywhere — x86_64, ARM64, WSL2, bare metal, containers.
• No Python. No GPU. No ML stack.

Full Pipeline (audio deconstruction with Demucs)

Everything above, plus:

• Python 3.10+
• pip packages: demucs, librosa, numpy, scipy, scikit-learn, torch
• ~2GB disk for PyTorch + Demucs model weights (downloaded on first run)
• Optional: NVIDIA GPU + CUDA toolkit for ~5× Demucs speedup

Install the Python deps:

pip install demucs librosa numpy scipy scikit-learn torch

If Python deps are missing, composition and rendering still work — you just can't do stem extraction. The skill should fail gracefully with a message, not a stack trace.

Full Pipeline (Audio Deconstruction)

If you have an MP3 and want to extract instruments from it, build sample racks, and compose with the extracted material — that's the full pipeline. It goes:

MP3 → Demucs (stem separation) → librosa (analysis) → sample slicing → Strudel composition → render → MP3

This is a 4–8 minute process for a typical track. See docs/pipeline.md for the complete stage-by-stage breakdown with commands, timings, and resource requirements.

Quick version

# 1. Separate stems (Python/Demucs)
python -m demucs input.mp3 --out ./stems

# 2. Analyze + slice (see docs/pipeline.md for details)
# Currently semi-manual — analysis scripts in development

# 3. Write composition referencing sliced samples
# 4. Render
bash scripts/dispatch.sh render my-composition.js 16 120

# 5. Convert
ffmpeg -i output.wav -c:a libmp3lame -q:a 2 output.mp3 -y

Timings (ballpark)

Total (4-min track, CPU): 4–8 minutes. Compose + render only (no Demucs): 2–3 minutes.

⚠️ Session Safety — READ THIS

The full pipeline takes 4–8 minutes. Composition + render alone takes 2–3 minutes.

DO NOT run this inline in a Discord channel interaction or primary OpenClaw session. The 30-second response timeout will kill the process mid-render. There is no supervisor to recover. The skill will appear broken — silence, no output, no error message.

How to run safely

From an OpenClaw agent (correct):

sessions_spawn({
  task: "Render strudel composition: /strudel dark ambient tension, 65bpm",
  mode: "run",
  runTimeoutSeconds: 600  // 10 minutes — generous for full pipeline
})

Background process (also correct):

exec({ command: "bash scripts/dispatch.sh render ...", background: true })

Direct CLI (fine for testing):

bash scripts/dispatch.sh render assets/compositions/fog-and-starlight.js 16 72

What to tell the user: "Rendering takes a few minutes — I'll post the audio when it's ready." Don't leave them hanging with no feedback.

What NOT to do

// WRONG — will timeout after 30s in Discord context
exec({ command: "bash scripts/dispatch.sh render ..." })

// WRONG — blocking the main session for minutes
// (anything inline that takes >30s)

Learning Resources

Detailed documentation lives in docs/:

Start with composition-guide.md if you're writing patterns. The space-separated vs angle-bracket distinction is the #1 source of bugs (gain explosions, distortion, memory crashes). The guide covers it with real case studies.

How It Works

The offline renderer uses node-web-audio-api (Rust-based Web Audio for Node.js) for real audio synthesis:

1. Pattern evaluation — @strudel/core + @strudel/mini + @strudel/tonal parse pattern code into timed "haps"
2. Audio scheduling — Each hap becomes either:
   • An oscillator (sine/saw/square/triangle) with ADSR envelope, biquad filter, stereo pan
   • A sample (AudioBufferSourceNode) from the samples directory, with pitch shifting
3. Offline rendering — OfflineAudioContext.startRendering() produces complete audio
4. Output — 16-bit stereo WAV at 44.1kHz → ffmpeg → MP3/Opus

Note on mini notation: The renderer explicitly calls setStringParser(mini.mini) after import because Strudel's npm dist bundles duplicate the Pattern class across modules. Same class of bug as openclaw#22790.

Composition Reference

Tempo

setcpm(120/4)  // 120 BPM

stack(
  s("bd sd [bd bd] sd").gain(0.4),           // drums (samples)
  s("[hh hh] [hh oh]").gain(0.2),            // hats
  note("c3 eb3 g3 c4")                       // melody
    .s("sawtooth")
    .lpf(sine.range(400, 2000).slow(8))      // filter sweep
    .attack(0.01).decay(0.3).sustain(0.2)    // ADSR envelope
    .room(0.4).delay(0.2)                    // space
    .gain(0.3)
)

Mini Notation Quick Ref

Mood → Parameter Decision Tree

Full tree: references/mood-parameters.md. Production techniques: references/production-techniques.md.

⚠️ Critical Pitfall: Gain Patterns

Use <> (slowcat) for sequential values, NOT spaces:

// ❌ WRONG — all values play simultaneously, causes clipping
s("kick").gain("0.3 0.3 0.5 0.3")

// ✅ RIGHT — one value per cycle
s("kick").gain("<0.3 0.3 0.5 0.3>")

Full list: docs/KNOWN-PITFALLS.md

Loudness Validation

Always check after rendering:

ffmpeg -i output.wav -af loudnorm=print_format=json -f null - 2>&1 | grep -E "input_i|input_tp"

Target: -16 to -10 LUFS, true peak below -1 dBTP. Above -5 LUFS = something is wrong.

Audio Deconstruction Pipeline

Full pipeline docs: references/integration-pipeline.md

Audio → Demucs (stems) → librosa (analysis) → strudel.json → Composition → Render

1. Stem separation — Demucs splits audio into vocals, drums, bass, other
2. Analysis — librosa extracts pitches, onsets, rhythm patterns
3. Sample mapping — Results written to strudel.json with root notes
4. Two paths:
   • Grammar extraction (through-composed music) → generative program capturing statistical DNA
   • Sample-based (stanzaic/repetitive music) → stem slices played back through Strudel

Requires Python stack: uv init && uv add demucs librosa scikit-learn soundfile

File Structure

src/runtime/
  chunked-render.mjs      — Chunked offline renderer (avoids OOM on long pieces)
  offline-render-v2.mjs    — Core offline renderer
  smoke-test.mjs           — 12-point smoke test
scripts/
  download-samples.sh      — Download dirt-samples (idempotent)
  samples-manage.sh        — Sample pack manager
  vc-play.mjs              — Stream audio to Discord VC
samples/                   — Sample packs + strudel.json (gitignored)
assets/compositions/       — 15 original compositions
src/compositions/          — Audio deconstructions
references/                — Mood trees, techniques, architecture
docs/
  KNOWN-PITFALLS.md        — Critical composition pitfalls
  ONBOARDING.md            — Machine-actor onboarding guide

Renderer Internals

Uses node-web-audio-api (Rust-based Web Audio for Node.js). No browser, no Puppeteer.

The renderer calls setStringParser(mini.mini) after import because Strudel's npm dist bundles duplicate the Pattern class across modules — the mini notation parser registers on a different copy than the one used by note() and s().

All synthesis is local and offline via OfflineAudioContext: oscillators, biquad filters, ADSR envelopes, AudioBufferSourceNode for samples, dynamics compression, stereo panning. Output: 16-bit stereo WAV at 44.1kHz.

Known Platform Issues

🔒 Security Model

Strudel compositions are JavaScript files executed by Node.js. They have the same access as any Node.js script:

• Filesystem: read/write access to the working directory
• Environment: can read environment variables
• Network: can make HTTP requests

For untrusted compositions:

• Run in a container or VM with no sensitive credentials in the environment
• Use OpenClaw's sub-agent isolation (each sub-agent gets its own process)
• Review composition code before rendering

For your own compositions: No special precautions needed — you wrote the code.

This is the same trust model as any programming language skill. The renderer itself is safe; the risk is in what compositions you choose to run.

Discord Integration

This skill uses OpenClaw's built-in Discord voice channel support for streaming. No separate BOT_TOKEN, DISCORD_TOKEN, or any Discord credentials are required. OpenClaw handles all Discord authentication and connection management. The skill simply produces audio files and hands them to OpenClaw's voice subsystem.

npm install safety

package.json contains no postinstall, preinstall, or lifecycle hooks. npm run setup runs npm install + scripts/download-samples.sh (downloads CC0 sample packs from known URLs).

What scripts/download-samples.sh fetches

The download script sparse-clones tidalcycles/Dirt-Samples from GitHub (CC-licensed) — specifically these directories: bd sd hh oh cp cr ride rim mt lt ht cb 808bd 808sd 808hc 808oh. This fetches ~153 WAV files (~11MB total). The script is idempotent (skips if samples already exist).

What scripts/samples-manage.sh does

The sample manager downloads additional packs from user-specified URLs with safety controls:

• Size limit: configurable via STRUDEL_MAX_DOWNLOAD_MB (default: 10GB)
• Host allowlist: optional STRUDEL_ALLOWED_HOSTS (comma-separated; empty = allow all)
• MIME validation: checks downloaded files are audio or archive types
• Path traversal protection: validates extracted paths don't escape the samples directory (zip-slip protection)

Concurrency

Only one render should be active per session at a time. If a user requests /strudel clone while a previous render is in progress:

1. Check for active sub-agents using subagents(action=list)
2. If a strudel render is running, respond: "🎵 A render is already in progress. Please wait for it to complete."
3. Do not dispatch a second render — disk and memory contention can cause artifacts or failures.

Why: Concurrent renders with default output paths both write to output.wav, causing the second to overwrite the first. Even with explicit paths, two simultaneous OfflineAudioContext processes double memory usage. Sample loading is per-process (no shared cache), so there's no corruption risk — but disk I/O contention on the output write is real.