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    "readmeSummary": "## Google Jobs Scraper\n\nA scraper that extracts job listings from the Google Jobs search panel into structured JSON: it crawls paginated Google Jobs results, parses each job card into full job metadata (title, employer, posting location as listed by the source, full description text), structured highlights (qualifications, responsibilities, benefits), raw tags (employment type, posting age, benefit labels) and parsed metadata (posting date, schedule type, benefit flags), direct application links to source sites and job boards, a unique job identifier, and search-level metadata (search query, searched location, country/language, timestamp, pages processed). Technical capabilities include paginated crawling of the Google Jobs results panel, domain-to-country handling, language/country targeting, location-radius and posted-within time-window filtering, automatic retry strategies for location-targeted searches, parsing of multi-source apply links, and normalization of highlights and tags into machine-readable fields suitable for aggregation, filtering, and downstream analysis.\n\n## Use cases\n\n- Job market research: track hiring trends by role, location, or industry  \n- Recruiting pipelines: feed job listings into applicant tracking or CRM systems  \n- Salary and benefits benchmarking: aggregate compensation and benefits signals across listings  \n- Competitive intelligence: monitor which companies are hiring for specific roles  \n- Academic research: analyze labor market dynamics at scale  \n- Find remote engineering or customer support roles and pull company/apply links  \n- Track healthcare or nursing job openings across a state or region with apply links  \n- Monitor a specific employer’s open roles and compare postings across sources  \n- Filter for recent listings (e.g., posted within the last few days) and collect structured highlights and apply options",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDTaOAgswoFZ7XwUjh+pw4gOuCmYR341NiF0MdMuhkPpAppryfw7/dG5AUetL+L8aMhYuS9RwuOYC5pg3lkXgiMycWvXmx1Gc0OXN7NC67wqdlfKHGlgN5KIa+z5GHqER/azlq9r5ZkOCbVXzFT6VmGi675Zz55TWkMAzEvema8f01Vn4ffv3z9+C1ev3fUTFj6a73O2onM8obiGc3vFHmVLBhFGblTUJU1wUVfTjMMWRFb8phNNxa5epGDrbgfDelYtu/JAUQWM4RjFYczmxTFLJ9t0/gnf0ajfe75+cngvrot0mshuj5/aY+GpTif8cdBFY5XrjIQTueQ9kyOaiRp \n"
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}