data-scraper-agent

You can automate scheduled web scraping via free GitHub Actions hosting, eliminating the need for paid servers. The agent runs on your configured schedule, automatically collecting and storing public data without manual intervention or infrastructure costs.

AI scoring for scraped data works by using batch Gemini Flash LLM calls to summarize, classify, and score collected items. The system also implements feedback-based preference learning, improving scoring accuracy over time based on your accept and reject decisions.

Yes, you can use GitHub Actions to run scheduled data collection for free. This approach eliminates paid hosting requirements by leveraging GitHub's native automation capabilities to execute your scraping workflows on a configurable schedule.

The best way to track product prices and monitor job boards is deploying an automated AI agent that scrapes public sources on a schedule. It collects, scores, and syncs the relevant listings directly to Google Sheets or Supabase for easy review.

Yes, automated scraping supports RSS feeds and APIs alongside standard websites. The agent automates the end-to-end collection, enrichment, and storage of public data from any website, API, or RSS feed on a configurable schedule.

Deduplicate URLs when scraping news feeds and GitHub releases by implementing native URL deduplication logic within the automated collection workflow. This prevents redundant entries from being stored in your target Notion, Google Sheets, or Supabase database.