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car-noise-pwa-builder

Scaffold a full-stack car-noise diagnostic PWA with client, server, and templates.

2|Updated Apr 26, 2026
Search Tags:#scaffolding#fft#microphone#pwa#websocket#raspberry-pi#car-noise
One-click install
npx skills add https://github.com/gaebalai/gaebalai-marketplace --skill car-noise-pwa-builder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: car-noise-pwa-builder
Source: https://github.com/gaebalai/gaebalai-marketplace/tree/main/plugins/car-can-checker/skills/car-noise-pwa-builder
Command: npx skills add https://github.com/gaebalai/gaebalai-marketplace --skill car-noise-pwa-builder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates scaffolding of a complete, full-stack PWA for car-noise diagnostics, including mic FFT spectrogram visualization, CAN data streaming from a Raspberry Pi via WebSocket, and offline-ready service worker setup.

Core Features & Use Cases

  • Automatic project scaffolding: generates a ready-to-run PWA skeleton with client, server, and templates.
  • Real-time data visualization: integrates microphone FFT spectrogram alongside CAN data (RPM, speed, steering angle, gear) for interactive analysis.
  • Data capture & export: records audio, logs CAN messages, and exports ZIP packages containing WAV, CSV, and metadata for easy sharing and analysis.
  • Offline support: service worker enables offline usage and resilient performance in automotive environments.

Quick Start

Provide a project name, the PI host, and a signal-mapping JSON to generate a complete car-noise PWA scaffold.

Frequently Asked Questions about car-noise-pwa-builder

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

FAQPage Schema
How do I build a PWA for car noise diagnostics with a microphone spectrogram?▼

To build a car noise diagnostic PWA, you can use a scaffolding tool to automatically generate a full-stack client and server skeleton. This setup includes a ready-to-run PWA structure with integrated microphone FFT spectrogram visualization.

Can I stream CAN data from a Raspberry Pi to a web app via WebSocket?▼

Yes, you can stream CAN data from a Raspberry Pi to a web app via WebSocket by generating a project scaffold configured for this architecture. The automated template sets up the TLS-enabled Raspberry Pi server and WebSocket connection to stream telemetry like RPM and speed.

How do I capture and export audio and CAN data from a web application?▼

You can capture and export audio and CAN data by running a generated car-noise PWA skeleton. The application records microphone audio and logs CAN messages, then exports a ZIP package containing WAV files, CSV logs, and metadata for analysis.

Does a Progressive Web App work offline for automotive data visualization?▼

A Progressive Web App works offline for automotive data visualization by utilizing a service worker. The generated car-noise PWA includes a pre-configured service worker that enables offline usage and ensures resilient performance in automotive environments.

What inputs do I need to generate a full-stack car noise diagnostic web app?▼

To generate a full-stack car noise diagnostic web app, you need to provide a project name, the Raspberry Pi host address, and a signal-mapping JSON. These inputs allow the scaffolding tool to configure the server and map CAN data correctly.

What is the best way to visualize FFT audio alongside CAN telemetry in a local development environment?▼

The best way to visualize FFT audio alongside CAN telemetry in local development is by using an automated scaffolding template. It generates a PWA that integrates real-time microphone FFT spectrograms with interactive CAN data like steering angle and gear.

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