data-scraper-agent

Automating data scraping involves using Python scripts with requests and BeautifulSoup to extract public data on a schedule. This skill handles scheduling, collection, and AI enrichment to provide insights from sources like job boards or prices.

Yes, you can use AI to enrich scraped web data by processing it with Gemini Flash. This free LLM scores, summarizes, classifies, and matches data items automatically, transforming raw public data into valuable insights.

Yes, this data scraping approach supports exporting results to Notion and Google Sheets. It provides storage options for collected and enriched data by integrating directly with Notion, Sheets, and Supabase.

Automated web data collection requires Python along with the requests, BeautifulSoup, and playwright libraries. These dependencies handle HTTP requests, HTML parsing, and browser automation for scraping public sources.

The best way to track price changes and job listings is building an automated scraper using Python and a free LLM. This approach collects data from public sources, enriches it with AI, and stores results in your preferred database.

No, you do not need to pay for an LLM to classify and match scraped data items. This skill uses Gemini Flash, a free LLM, to handle AI enrichment tasks like scoring, summarizing, classifying, and matching data.