This project focused on the technical core of SEO auditing: safe crawling, modular analysis, resumable runs, and outputs that can feed both internal review and client deliverables.
Problem
SEO teams need more than a site crawl. They need reliable collection, analyzers that can be toggled per job, and reporting outputs that reduce manual synthesis work after the crawl is finished.
Solution
I built an asynchronous crawler with bounded queues, per-domain throttling, and optional JavaScript rendering. Results flowed through an event-driven analyzer system so on-page SEO, link health, and performance metrics could be added without rewriting the crawl engine.
Crawl scale
1k+ pages
Render mode
HTTP + optional JS
Persistence
JSON + SQLite
Outputs
Slides, email, metrics
What stands out
- The crawl pipeline was memory-safe because analyzers consumed results through a bounded queue.
- Resume and discovery modes made long-running audits practical instead of fragile.
- Reporting flattened metrics into template-ready placeholders for Slides and email drafts.
- Structured logs and recent run summaries improved debugging and operational visibility.
Note
Relationship to the audit platform
This case study is written as the crawler and reporting engine itself, while the separate audit automation platform project covers the end-to-end service layer and lead-delivery workflow.
Outcome
The result is a reusable SEO diagnostics engine that can run locally, support cloud deployment later, and give teams a faster path from crawl to decision-ready reporting.
