The skill helps choose the right crawler type for the target site, define routing rules for list pages versus detail pages, manage retries, and avoid wasting headless-browser resources on pages that only need HTTP parsing. It also helps structure output so downstream systems receive normalized records instead of a pile of ad hoc HTML fragments. For research and scraping workloads, that distinction matters because the expensive part is rarely the first request; it is maintaining quality and throughput across thousands of URLs.

Outputs can include JSON datasets, cleaned page records, crawl logs, request queue state, extracted entities, and evidence about failures such as blocked requests or selector drift. Integration points include Node.js data pipelines, Apify Actors, Playwright-based extraction steps, proxy layers, and downstream analytics or retrieval systems that ingest crawl results. Use this skill when the task requires coordinated crawling, browser-aware extraction, and repeatable collection architecture rather than a one-off scrape script.