Lighthouse Check

Abstract

1. Introduction

This project provides two ways of running audits - locally in your own environment or remotely via Foo's Automated Lighthouse Check API. For basic usage, running locally will suffice, but if you'd like to maintain a historical record of Lighthouse audits and utilize other features, you can run audits remotely by following the steps and examples.

2. Objective

An NPM module for automated Lighthouse audits.

This project demonstrates how JavaScript, Node.js can be applied to a real-world Digital Marketing & SEO problem.

3. Key Features / Modules

• Simple usage - only one parameter required.
• Run multiple Lighthouse audits with one command.
• Optionally run Lighthouse remotely and save audits with the Foo's Automated Lighthouse Check API.
• Optionally save an HTML report locally.
• Optionally save an HTML report in an AWS S3 bucket.
• Easy setup with Slack Webhooks. Just add your Webhook URL and lighthouse-check will send results and optionally include versioning data like branch, author, PR, etc (typically from GitHub).
• PR comments of audit scores.
• NPM module for programmatic usage.
• CLI - see CLI Usage.
• Docker - see Docker Usage.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/foo-software/lighthouse-check.git
cd lighthouse-check

npm install @foo-software/lighthouse-check

import { lighthouseCheck } from '@foo-software/lighthouse-check';

(async () => {
  const response = await lighthouseCheck({
    urls: [
      'https://www.foo.software/lighthouse',
      'https://www.foo.software/contact',
    ],
  });

  console.log('response', response);
})();

$ lighthouse-check --urls "https://www.foo.software/lighthouse,https://www.foo.software/contact"

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by foo-software and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.