Scoutly

Abstract

1. Introduction

Scoutly audits a website by crawling its HTML pages, analyzing common SEO problems, and checking discovered links and images.

Scoutly provides a script-friendly CLI, a keyboard-driven terminal interface, and an idiomatic asynchronous Rust library.

image alt text, thin content, and Open Graph metadata.

2. Objective

A fast, lightweight CLI website crawler and SEO analyzer built with Go

This project demonstrates how Rust can be applied to a real-world Digital Marketing & SEO problem.

3. Key Features / Modules

• Crawl same-origin HTML pages with configurable depth, page, concurrency, and
• Find broken or redirected links and validate discovered images.
• Flag common SEO problems involving titles, meta descriptions, H1 headings,
• Respect robots.txt rules and discover pages from XML and gzip sitemaps.
• Explore results interactively or emit text and machine-readable JSON reports.

4. Technology Stack

5. System Requirements

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

• Rust toolchain (rustup / cargo)
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/nelsonlaidev/scoutly.git
cd scoutly

brew install --cask nelsonlaidev/tap/scoutly

npm install --global @nelsonlaidev/scoutly

cargo install scoutly --locked

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 nelsonlaidev 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.