data-scraper-agent

Automate web scraping by configuring an agent to collect public data and push results to Notion. This eliminates manual data entry by scheduling automated workflows that extract, enrich, and store items directly into your Notion database.

Yes, you can schedule data collection workflows for free using GitHub Actions. This approach automates scraping tasks on a custom schedule without manual intervention or hosting costs, running serverless jobs to collect data consistently.

The best way to score and summarize scraped job listings is using AI-powered enrichment. By applying free Gemini Flash models, you can classify and summarize collected items based on your custom priorities and context to identify relevant roles.

Yes, this scraping approach works with e-commerce sites and public APIs. It automates the end-to-end collection of public data from arbitrary sources, allowing you to track product price drops or ingest API feeds consistently.

To avoid hitting API quotas when batch processing scraped data, implement rate-limited LLM API calls with multi-model fallback chains. This ensures batch processing avoids quota exhaustion while maintaining continuous data enrichment.

The scraper improves matching accuracy through adaptive learning from user feedback. By providing feedback on past collected items stored in Google Sheets or Supabase, future results are automatically refined to better match your priorities.