Job Posting Signal Normalizer
Pricing
Pay per event
You can access the Job Posting Signal Normalizer programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youβll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "1.0", "x-build-id": "sa7tEud38c2Vyicxc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/zentrafoundry~job-posting-signal-normalizer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-zentrafoundry-job-posting-signal-normalizer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/zentrafoundry~job-posting-signal-normalizer/runs": { "post": { "operationId": "runs-sync-zentrafoundry-job-posting-signal-normalizer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/zentrafoundry~job-posting-signal-normalizer/run-sync": { "post": { "operationId": "run-sync-zentrafoundry-job-posting-signal-normalizer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "sourceMode" ], "properties": { "searchKeywords": { "title": "Job Company Signal keywords", "type": "array", "description": "Buyer-relevant keywords used to focus the records returned by this product.", "default": [ "source-backed signal", "buyer fit" ], "items": { "type": "string" } }, "taskIntent": { "title": "Job Company Signal task intent", "type": "string", "description": "Stable product-specific purpose for this saved Apify task.", "default": "buyer-ready-product-run" }, "sourceMode": { "title": "Run sample or approved live sources", "enum": [ "sample", "startUrls" ], "type": "string", "description": "Sample emits public-safe Job Company Signal rows. Approved live source mode keeps the same output fields and only uses owner-approved public URLs.", "default": "sample" }, "outputMode": { "title": "Job Company Signal output mode", "enum": [ "sample-records", "buyer-ready-records" ], "type": "string", "description": "Use sample records for Apify Store QA or buyer-ready records for approved Job Company Signal delivery.", "default": "sample-records" }, "startUrls": { "title": "Approved Job Company Signal source URLs", "type": "array", "description": "Public URLs to use for live Job Company Signal extraction after source-policy approval. Leave empty for sample mode.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "title": "URL", "type": "string", "description": "Approved public Job Company Signal source URL." } } }, "default": [] }, "maxItems": { "title": "Maximum Job Company Signal rows", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Caps the number of Job Company Signal rows written to the dataset.", "default": 1 }, "perSourceLimit": { "title": "Maximum rows per source", "minimum": 1, "maximum": 100, "type": "integer", "description": "Caps validated rows from any one source before cross-source deduplication.", "default": 25 }, "maxTotalChargeUsd": { "title": "Maximum total charge (USD)", "minimum": 0.01, "maximum": 1000, "type": "number", "description": "Buyer-selected spend ceiling; the Apify run-level maximum remains authoritative.", "default": 5 }, "overallTimeoutSecs": { "title": "Overall timeout seconds", "minimum": 30, "maximum": 3600, "type": "integer", "description": "Stops additional source work once the bounded run deadline is reached.", "default": 900 }, "requestTimeoutSecs": { "title": "Source request timeout seconds", "minimum": 5, "maximum": 120, "type": "integer", "description": "Timeout applied independently to each approved source request.", "default": 30 }, "maxRequestRetries": { "title": "Maximum source retries", "minimum": 0, "maximum": 5, "type": "integer", "description": "Bounded retry count for transient source failures.", "default": 2 }, "sinceLastRun": { "title": "Only emit new logical records", "type": "boolean", "description": "Uses stable Actor state to skip logical records delivered by earlier runs.", "default": false }, "deltaMode": { "title": "Delta mode", "type": "boolean", "description": "Preserves stable deduplication keys for recurring tasks and schedules.", "default": true } } }, "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.
You can download the OpenAPI definitions for Job Posting Signal Normalizer from the options below:
If youβd like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: