# Public Job Posting Detail Agent (`jacksu/public-job-posting-detail-agent`) Actor Extract one structured public job posting record from each user-provided job detail URL, with title, company, location, salary, skills, dates, apply link, evidence, and change hash. - **URL**: https://apify.com/jacksu/public-job-posting-detail-agent.md - **Developed by:** [jack su](https://apify.com/jacksu) (community) - **Categories:** Jobs, Business, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 useful job posting results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Public Job Posting Detail Agent Extract one structured job posting record from each user-provided public job detail URL. The Actor reads public HTML and Schema.org `JobPosting` evidence, then returns title, company, location, remote/visa signals, employment type, salary hints, dates, apply URL, skills, evidence snippets, and a stable hash. This product is intentionally different from the portfolio's site-level Hiring Signal Actor. It does not discover careers pages, crawl job lists, count all open roles, or score company hiring intensity. It only analyzes the job detail URLs you provide. ### What It Returns - `jobTitle`, `companyName`, `locationSummary`, `employmentType`, and `descriptionSnippet`. - `salarySummary`, `datePosted`, `validThrough`, `applyUrl`, `remoteSignal`, and `visaSignal` when visible. - `skills`, `matchedSkills`, and `matchedLocations` for filtering. - `responsibilities`, `qualifications`, `evidenceSnippets`, and `evidenceUrls`. - `jobHash` and `changeStatus` for monitoring job-posting changes. ### Good Fits - Normalize public job detail URLs that a user, CRM, or AI agent already has. - Check whether a role matches target skills or target locations. - Monitor public job detail records for changes without charging unchanged records. - Convert JobPosting JSON-LD and visible public HTML into a compact dataset. ### Not A Fit - LinkedIn, Indeed, Google Jobs, Facebook, or other job-board search/list scraping. - Company-wide hiring intensity analysis. Use the site-level Hiring Signal Actor for that task. - Candidate data, resumes, recruiter-private contact enrichment, login-only pages, or application form submission. ### Safety Boundary - Public HTTP and HTTPS job detail pages only. - No login, cookies, JavaScript execution, form submission, CAPTCHA bypassing, account creation, candidate enrichment, or private-person profiling. - Query strings, fragments, URL credentials, path parameters, private networks, localhost, `.local`, account-like sensitive paths, and token-like path segments are rejected or safely redacted. - HTML/text responses are capped at 3 MB. - The Actor does not follow related-job, more-jobs, or all-jobs links. ### Pricing Behavior The pay-per-event setup charges only for useful public job posting records: - `apify-actor-start`: charged once when a run starts. - `useful-job-posting-result`: charged only for a new or changed job detail record with enough public evidence and any required skill/location match. The Actor intentionally does not configure `apify-default-dataset-item`, so errors, duplicate inputs, unchanged records, focus misses, blocked platforms, and low-evidence pages can be written without charging the useful-result event. ### Example Input ```json { "jobUrls": ["https://www.mozilla.org/en-US/careers/position/gh/7622995/"], "focusSkills": ["ai"], "focusLocations": ["remote"], "requestTimeoutSecs": 20 } ```` # Actor input Schema ## `jobUrls` (type: `array`): Public HTTP/HTTPS job detail page URLs. Query parameters, fragments, credentials, path params, private-network hosts, and token-like account paths are rejected. ## `focusSkills` (type: `array`): Optional skill terms that must appear in the extracted job evidence before the useful event is charged, such as Python, TypeScript, SEO, sales, or Kubernetes. ## `focusLocations` (type: `array`): Optional location terms that must appear in the extracted job evidence before the useful event is charged, such as remote, London, New York, Germany, or Singapore. ## `previousJobPostingRecords` (type: `array`): Optional previous records from this Actor. If the stable jobHash is unchanged, the result is written without charging the useful event. ## `requestTimeoutSecs` (type: `integer`): Maximum time in seconds to wait for the public page response. ## Actor input object example ```json { "jobUrls": [ "https://www.mozilla.org/en-US/careers/position/gh/7622995/" ], "focusSkills": [], "focusLocations": [], "previousJobPostingRecords": [], "requestTimeoutSecs": 20 } ``` # Actor output Schema ## `datasetId` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("jacksu/public-job-posting-detail-agent").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("jacksu/public-job-posting-detail-agent").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call jacksu/public-job-posting-detail-agent --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jacksu/public-job-posting-detail-agent", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Public Job Posting Detail Agent", "description": "Extract one structured public job posting record from each user-provided job detail URL, with title, company, location, salary, skills, dates, apply link, evidence, and change hash.", "version": "0.1", "x-build-id": "F13XR4S72QsI4IqBL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jacksu~public-job-posting-detail-agent/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jacksu-public-job-posting-detail-agent", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jacksu~public-job-posting-detail-agent/runs": { "post": { "operationId": "runs-sync-jacksu-public-job-posting-detail-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jacksu~public-job-posting-detail-agent/run-sync": { "post": { "operationId": "run-sync-jacksu-public-job-posting-detail-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "jobUrls" ], "properties": { "jobUrls": { "title": "Job detail URLs", "minItems": 1, "maxItems": 20, "type": "array", "description": "Public HTTP/HTTPS job detail page URLs. Query parameters, fragments, credentials, path params, private-network hosts, and token-like account paths are rejected.", "items": { "type": "string" }, "default": [ "https://www.mozilla.org/en-US/careers/position/gh/7622995/" ] }, "focusSkills": { "title": "Focus skills", "type": "array", "description": "Optional skill terms that must appear in the extracted job evidence before the useful event is charged, such as Python, TypeScript, SEO, sales, or Kubernetes.", "items": { "type": "string" }, "default": [] }, "focusLocations": { "title": "Focus locations", "type": "array", "description": "Optional location terms that must appear in the extracted job evidence before the useful event is charged, such as remote, London, New York, Germany, or Singapore.", "items": { "type": "string" }, "default": [] }, "previousJobPostingRecords": { "title": "Previous job posting records", "type": "array", "description": "Optional previous records from this Actor. If the stable jobHash is unchanged, the result is written without charging the useful event.", "items": { "type": "object" }, "default": [] }, "requestTimeoutSecs": { "title": "Request timeout", "minimum": 5, "maximum": 60, "type": "integer", "description": "Maximum time in seconds to wait for the public page response.", "default": 20 } } }, "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 } } } } } } } } } } ```