What problem does it solve? Manually monitoring websites for new jobs, prices, news, or listings is repetitive and easy to forget. This Skill generates a complete automated data collection agent that scrapes public sources on a schedule, enriches each item with an LLM, stores results in a database, and learns from your feedback — all running free on GitHub Actions. ## Core Features & Use Cases - Three-Layer Agent Architecture: Generates a COLLECT → ENRICH → STORE pipeline with pluggable scraper sources (REST API, HTML, RSS, Playwright), batched Gemini analysis, and Notion/Sheets/Supabase storage. - Free-Tier Engineering: Includes a Gemini model fallback chain, batch API calls (5 items per request), rate limiting, and URL deduplication to stay within free quotas. - Feedback Learning: Converts your accept/reject decisions into prompt bias so scoring improves over time, persisted in a JSON file committed by GitHub Actions. - Use Case: Ask for an agent that monitors Hacker News for AI startup funding news — you get a full repo with config.yaml, scraper sources, AI pipeline, Notion sync, and a cron workflow. ## Quick Start Build me an agent that scrapes new GitHub repos tagged with 'llm', summarizes each one with AI, and saves them to Notion every three hours.