beatlab-pipeline

Validate, render, and export beat data from beat.json to MIDI and WAV.

Updated Jan 15, 2026
One-click install
npx skills add https://github.com/ryok/claude-beatlab --skill beatlab-pipeline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: beatlab-pipeline
Source: https://github.com/ryok/claude-beatlab/tree/main/.claude/skills/beatlab-pipeline
Command: npx skills add https://github.com/ryok/claude-beatlab --skill beatlab-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill orchestrates a deterministic BeatLab pipeline to validate, render, and export beat data from beat.json, removing guesswork from reproducible beat production.

Core Features & Use Cases

  • Deterministic validation and normalization of pianoSequence and drumSequence data.
  • ASCII grid rendering for quick visual verification.
  • MIDI and WAV export for DAW workflows, with optional MP3 via ffmpeg.
  • Useful in development, testing, and CI to reproduce beat artifacts from a single source file.

Quick Start

Use the BeatLab pipeline to validate, visualize, and export beat artifacts from beat.json:

  • uv run python .claude/skills/beatlab-pipeline/scripts/validate.py <beat.json> --inplace
  • uv run python .claude/skills/beatlab-pipeline/scripts/render_grid.py <beat.json>
  • uv run python .claude/skills/beatlab-pipeline/scripts/export_midi.py <beat.json> <out.mid>
  • uv run python .claude/skills/beatlab-pipeline/scripts/render_wav.py <beat.json> <out.wav>
  • ffmpeg -y -i <out.wav> <out.mp3>

Frequently Asked Questions about beatlab-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate and normalize beat data in a JSON file?▼

The pipeline renders an ASCII grid from your beat.json file, allowing quick visual verification of note placement and sequence timing without needing to open a DAW or audio editor.

What's the best way to export MIDI directly from a beat JSON file?▼

You can render WAV audio from beat.json using a Python rendering script executed through uv, generating a reproducible .wav file; optional MP3 export additionally requires FFmpeg installed on your system.

Do I need any special dependencies to run deterministic beat validation in CI?▼

The pipeline provides deterministic validation and normalization of pianoSequence and drumSequence data, ensuring that rendering and exporting audio artifacts from a single beat.json source file produces identical results across runs.

Can I use ASCII grid rendering to visually verify MIDI sequence data?▼

Yes, the pipeline includes an ASCII grid rendering script that accepts beat.json and outputs a text-based visual grid, allowing quick visual verification of sequence data before MIDI or WAV export.