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Shadow Extractor
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3
Pricing
Pay per usage
Pricing
Pay per usage
Rating
0.0
(0)
Developer
Shadow Extractor
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
a month ago
Last modified
Categories
Share
Choose Search jobs to discover listings, Direct job details when you already have URLs or IDs, or Auto detect to let the actor choose from your input.
Indeed country/domain to use for generated search and detail URLs.
Job titles or keywords for SEARCH mode. Add one or many terms such as software engineer, nurse, data analyst, or customer support.
[ "python developer"][ "python developer"]Cities, states, countries, or Remote. Each search query is combined with each location.
[ "New York, NY"][ "New York, NY"]Maximum number of paid job results saved to the default dataset.
Paste direct job URLs or Indeed search URLs. Direct job URLs work best with the Full details option below.
[]Pagination safety limit per query/location or search URL. Increase for larger searches.
Indeed date filter. Leave empty to avoid a date filter.
Indeed job type filter.
Remote preference. Best-effort because Indeed varies filters by country.
Search radius in miles for Indeed domains that support it.
Sort order for generated search URLs.
Fast returns listing cards only. Full details adds the complete description, public emails and phones, available company images, salary data, requirements, benefits, skills, and apply links.
Parse salary text into min/max/unit/currency and annualized fields.
Extract skills from job descriptions and attributes using rule-based dictionaries.
Follow an available apply link to identify the final employer or ATS destination. Keep it off when you only need listing data.
Add public employer metadata such as website, social links, rating, size, industry, description, logo, header image, addresses, and company-level contacts when Indeed publishes them.
Optional matching input. Add target skills and salary to get a basic candidateFit object on each job.
{ "skills": [], "targetSalaryAnnual": null}{ "skills": [ "python", "sql", "aws" ], "targetSalaryAnnual": 120000}Skip duplicate job keys/canonical URLs and title/company/location duplicates.
Compact keeps only populated fields for a clean table. Full keeps a stable wide schema with empty placeholders for integrations.
Compare the current run with the previous run stored in the default key-value store. Keep off for random tests.
Include selected raw parser/debug fields. This can increase dataset size and is usually only useful for development.
Maximum number of source requests processed at once. The default is recommended for normal runs.
Retry budget for temporary source or connection errors.