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Shadow Extractor
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Shadow Extractor
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You can access the 3 programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youโll need an Apify account and your API token, found in API & Integrations in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.1", "x-build-id": "DkUrjcFu5ZSsYFg5F" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shadowextractor~indeed-jobs-intelligence-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shadowextractor-indeed-jobs-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/shadowextractor~indeed-jobs-intelligence-scraper/runs": { "post": { "operationId": "runs-sync-shadowextractor-indeed-jobs-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/shadowextractor~indeed-jobs-intelligence-scraper/run-sync": { "post": { "operationId": "run-sync-shadowextractor-indeed-jobs-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "๐งญ What do you want to do?", "enum": [ "AUTO", "SEARCH", "DETAIL" ], "type": "string", "description": "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.", "default": "AUTO" }, "country": { "title": "๐ Indeed country", "enum": [ "us", "gb", "ca", "au", "de", "fr", "nl", "es", "it", "br", "in", "sg", "za" ], "type": "string", "description": "Indeed country/domain to use for generated search and detail URLs.", "default": "us" }, "queries": { "title": "๐ Search query / job title", "type": "array", "description": "Job titles or keywords for SEARCH mode. Add one or many terms such as software engineer, nurse, data analyst, or customer support.", "items": { "type": "string" }, "default": [ "python developer" ] }, "locations": { "title": "๐ Location(s)", "type": "array", "description": "Cities, states, countries, or Remote. Each search query is combined with each location.", "items": { "type": "string" }, "default": [ "New York, NY" ] }, "maxResults": { "title": "๐ฏ Number of jobs to extract", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of paid job results saved to the default dataset.", "default": 10 }, "startUrls": { "title": "๐ Indeed URLs", "type": "array", "description": "Paste direct job URLs or Indeed search URLs. Direct job URLs work best with the Full details option below.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "jobIds": { "title": "๐งพ Job IDs", "type": "array", "description": "Indeed job keys such as de07417d37bb4b34.", "items": { "type": "string" }, "default": [] }, "maxPagesPerSearch": { "title": "๐ Pages per search", "minimum": 1, "maximum": 100, "type": "integer", "description": "Pagination safety limit per query/location or search URL. Increase for larger searches.", "default": 1 }, "postedWithinDays": { "title": "๐๏ธ Posted within", "enum": [ "", "1", "3", "7", "14", "30" ], "type": "string", "description": "Indeed date filter. Leave empty to avoid a date filter.", "default": "7" }, "jobType": { "title": "๐ผ Job type", "enum": [ "", "fulltime", "parttime", "contract", "temporary", "internship", "commission" ], "type": "string", "description": "Indeed job type filter.", "default": "" }, "remote": { "title": "๐ Remote filter", "enum": [ "", "remote", "hybrid", "on_site" ], "type": "string", "description": "Remote preference. Best-effort because Indeed varies filters by country.", "default": "" }, "radius": { "title": "๐ Search radius", "minimum": 0, "maximum": 100, "type": "integer", "description": "Search radius in miles for Indeed domains that support it.", "default": 25 }, "sort": { "title": "โ๏ธ Sort results", "enum": [ "relevance", "date" ], "type": "string", "description": "Sort order for generated search URLs.", "default": "relevance" }, "enrichmentMode": { "title": "๐ฌ Data depth", "enum": [ "fast", "full" ], "type": "string", "description": "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.", "default": "fast" }, "normalizeSalary": { "title": "๐ฐ Normalize salary", "type": "boolean", "description": "Parse salary text into min/max/unit/currency and annualized fields.", "default": true }, "extractSkills": { "title": "๐ง Extract skills", "type": "boolean", "description": "Extract skills from job descriptions and attributes using rule-based dictionaries.", "default": true }, "resolveApplyUrls": { "title": "๐ Resolve apply URLs", "type": "boolean", "description": "Follow an available apply link to identify the final employer or ATS destination. Keep it off when you only need listing data.", "default": false }, "enrichCompanyProfiles": { "title": "๐ข Add company profile data", "type": "boolean", "description": "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.", "default": false }, "candidateProfile": { "title": "๐ฏ Candidate profile", "type": "object", "description": "Optional matching input. Add target skills and salary to get a basic candidateFit object on each job.", "default": { "skills": [], "targetSalaryAnnual": null } }, "dedupe": { "title": "๐งน Deduplicate jobs", "type": "boolean", "description": "Skip duplicate job keys/canonical URLs and title/company/location duplicates.", "default": true }, "outputMode": { "title": "๐ฆ Output mode", "enum": [ "compact", "full" ], "type": "string", "description": "Compact keeps only populated fields for a clean table. Full keeps a stable wide schema with empty placeholders for integrations.", "default": "compact" }, "enableDeltaMonitoring": { "title": "๐ Delta monitoring", "type": "boolean", "description": "Compare the current run with the previous run stored in the default key-value store. Keep off for random tests.", "default": false }, "rawOutput": { "title": "๐งช Include raw debug fields", "type": "boolean", "description": "Include selected raw parser/debug fields. This can increase dataset size and is usually only useful for development.", "default": false }, "maxConcurrency": { "title": "โก Max concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of source requests processed at once. The default is recommended for normal runs.", "default": 6 }, "maxRetries": { "title": "๐ Max retries", "minimum": 0, "maximum": 20, "type": "integer", "description": "Retry budget for temporary source or connection errors.", "default": 3 }, "proxyConfiguration": { "title": "๐ Connection settings", "type": "object", "description": "Connection settings for cloud and local runs. Keep the default configuration for normal use.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
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