job-search

Automated job searching works by scraping job boards and filtering listings against your user-defined preferences and resume data. It extracts structured job data, scores fit, resolves direct employer URLs, and presents curated results with networking insights.

Preventing duplicate job listings is handled automatically through job history tracking. The skill maintains a record of found jobs during daily automated runs, ensuring you only see new, curated matching openings without redundant entries.

Yes, browser automation tools are required to scrape job boards and resolve direct employer URLs for effective matching. You also need to provide access to user profile data so the skill can evaluate listings against your resume.

Yes, smart filtering applies criteria like salary, location, and dealbreakers to narrow down scraped job board results. This ensures the curated list only includes openings matching your specific preferences and requirements.

Fit scoring evaluates job listings by comparing extracted structured data against your user-defined preferences and resume data. It scores each opening to help you prioritize the most relevant career opportunities from the automated search results.

Limitations include strict dependencies on browser automation tools and continuous access to user profile data. Without these inputs, the automated scraping, fit scoring, and direct employer URL resolution cannot function effectively.