# LinkedIn Company Hiring Tracker (`coregent/linkedin-company-hiring-tracker`) Actor Track open LinkedIn jobs for a list of companies and get one clean hiring-signal row per company - open roles, top functions, locations, seniority mix, remote/hybrid count, and change since last run. No LinkedIn login or cookies. - **URL**: https://apify.com/coregent/linkedin-company-hiring-tracker.md - **Developed by:** [Delowar Munna](https://apify.com/coregent) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.60 / 1,000 company-results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## LinkedIn Company Hiring Tracker ![LinkedIn Company Hiring Tracker](https://raw.githubusercontent.com/coregentdevspace/linkedin-company-hiring-tracker-assets/main/thumbnail-linkedin-company-hiring-tracker.jpg) Track **open LinkedIn jobs for a list of companies** and get back **one clean hiring-signal row per company** — total open roles, newest/oldest posting date, top hiring functions, top locations, seniority mix, remote/hybrid/on-site mix, a transparent **0–100 hiring-signal score**, and **change since the last tracked run**. Built for **B2B sales teams, recruiters, staffing agencies, market researchers, and competitor monitoring**. This is a **company-level hiring signal tracker — not a generic job feed**. You get a watchlist-ready summary (_who is hiring, where, in which functions, and whether hiring is increasing_), not thousands of individual job rows. **No LinkedIn login, no cookies, no session IDs.** The actor reads LinkedIn's public company and guest jobs surfaces over HTTP. You pay one flat event per saved company row. ### ✨ Why this tracker - **One row per company** — open roles, function/seniority/location/remote mix, and a hiring signal, all flat and CSV-ready. No nested objects. - **Company-first input** — paste LinkedIn company URLs (recommended) or plain company names (best-effort resolution). - **Change tracking** — compares each company to its previous run via a named key-value store, so scheduled runs show hiring momentum (`increased` / `decreased` / `unchanged` / `first_seen`). - **Transparent hiring-signal score** — rule-based (no AI), explained below. - **Pay-Per-Event** — one flat `company-result` event per saved company. Duplicates, failed inputs, and filtered companies are never charged. - **No login / cookies / sessions** — just company URLs or names. --- ### 🚀 Quick start — sample inputs #### Example 1 — track a watchlist by company URL ```json { "companyUrls": ["https://www.linkedin.com/company/atlassian/", "https://www.linkedin.com/company/canva/"], "maxCompanies": 100, "maxJobsPerCompany": 250, "postedDate": "past30d", "includeJobSamples": true, "includeChangeTracking": true, "stateStoreName": "linkedin-company-hiring-tracker-state", "minOpenJobs": 1, "deduplicateCompanies": true, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Example 2 — by company name + custom residential proxy via your own provider ```json { "companyNames": ["Stripe", "Notion", "Figma"], "maxCompanies": 50, "maxJobsPerCompany": 150, "postedDate": "past7d", "minOpenJobs": 5, "includeChangeTracking": false, "proxyConfiguration": { "useApifyProxy": false, "proxyUrls": ["http://user:pass@proxy.iproyal.com:12321"] } } ``` > Provide **at least one** of `companyUrls` or `companyNames`. If you provide both, URLs are processed first and companies are deduplicated so each is processed and charged once. > The actor blocks Apify Residential proxy; if you need residential routing, supply your own provider via `proxyConfiguration.proxyUrls`. See **🚦 Proxy policy** below. *** ### 📦 Output The dataset has one view: **Company hiring signals** — one flat row per company. ![LinkedIn Company Hiring Tracker — company hiring signals table view](https://raw.githubusercontent.com/coregentdevspace/linkedin-company-hiring-tracker-assets/main/linkedin-company-hiring-tracker-output-overview.png) #### Sample record — Company hiring signals ```json { "input_company_url": "https://www.linkedin.com/company/atlassian/", "input_company_name": null, "company_name": "Atlassian", "company_linkedin_url": "https://www.linkedin.com/company/atlassian/", "company_slug": "atlassian", "company_id": "1679", "company_industry": "Software Development", "company_size": "10001+ employees", "company_headquarters": "Sydney, NSW", "open_jobs_total": 148, "jobs_scanned": 148, "jobs_scan_limited": false, "newest_job_posted_at": "2026-05-24", "oldest_job_posted_at": "2026-04-28", "top_function_1": "engineering", "top_function_1_count": 54, "top_function_2": "sales", "top_function_2_count": 22, "top_function_3": "product", "top_function_3_count": 16, "top_location_1": "Sydney, NSW", "top_location_1_count": 38, "top_location_2": "San Francisco, CA", "top_location_2_count": 21, "remote_jobs_count": 18, "hybrid_jobs_count": 42, "onsite_jobs_count": 88, "seniority_entry_count": 5, "seniority_mid_count": 76, "seniority_senior_count": 49, "seniority_manager_count": 18, "sample_job_title_1": "Senior Software Engineer", "sample_job_url_1": "https://www.linkedin.com/jobs/view/1234567890/", "sample_job_title_2": "Product Manager", "sample_job_url_2": "https://www.linkedin.com/jobs/view/1234567891/", "sample_job_title_3": "Enterprise Account Executive", "sample_job_url_3": "https://www.linkedin.com/jobs/view/1234567892/", "previous_open_jobs_total": 121, "open_jobs_change": 27, "open_jobs_change_label": "increased", "hiring_signal_score": 95, "hiring_signal_label": "Very strong", "reason_tags": "many_open_roles|hiring_increased|fresh_jobs|multi_function_hiring|senior_hiring|remote_or_hybrid_roles|engineering_heavy", "source_type": "company_url", "scrape_status": "success", "error_message": null, "scraped_at": "2026-05-25T00:00:00.000Z" } ``` #### Output fields - **Input echo**: `input_company_url`, `input_company_name`, `source_type` - **Company identity**: `company_name`, `company_linkedin_url`, `company_slug`, `company_id`, `company_industry`, `company_size`, `company_headquarters` - **Open-roles**: `open_jobs_total`, `jobs_scanned`, `jobs_scan_limited`, `newest_job_posted_at`, `oldest_job_posted_at` - **Function mix**: `top_function_1..3` + `_count` - **Location mix**: `top_location_1..2` + `_count` - **Workplace mix**: `remote_jobs_count`, `hybrid_jobs_count`, `onsite_jobs_count` - **Seniority mix**: `seniority_entry_count`, `seniority_mid_count`, `seniority_senior_count`, `seniority_manager_count` - **Samples** (if enabled): `sample_job_title_1..3`, `sample_job_url_1..3` - **Change tracking**: `previous_open_jobs_total`, `open_jobs_change`, `open_jobs_change_label` - **Signal**: `hiring_signal_score`, `hiring_signal_label`, `reason_tags` - **Status**: `scrape_status`, `error_message`, `scraped_at` *** ### 🎯 Hiring-signal score Transparent rule-based score (0–100) computed from the company aggregates — no AI, no external enrichment. | Signal | Points | | ------------------------------------------ | -----: | | 50+ open roles | +40 | | 20–49 open roles | +30 | | 5–19 open roles | +20 | | 1–4 open roles | +10 | | Open roles increased by 10+ since last run | +20 | | Open roles increased by 1–9 since last run | +10 | | Newest job posted within the last 7 days | +10 | | At least 3 functions hiring | +10 | | Senior + manager roles present, count ≥ 5 | +10 | | Remote or hybrid roles present | +5 | Score is capped at 100. The change component is only applied when a previous snapshot exists (otherwise the row is tagged `first_seen`). **Labels**: `Very strong` (80–100) · `Strong` (60–79) · `Moderate` (35–59) · `Weak` (1–34) · `No visible hiring` (0). `reason_tags` is a **pipe-separated** list explaining the score — e.g. `many_open_roles`, `moderate_open_roles`, `few_open_roles`, `hiring_increased`, `hiring_decreased`, `first_seen`, `fresh_jobs`, `multi_function_hiring`, `senior_hiring`, `remote_or_hybrid_roles`, `engineering_heavy`, `sales_heavy`, `scan_limited`. *** ### 🔁 Change tracking When `includeChangeTracking` is on, the actor stores each company's open-jobs count in a **named key-value store** (`stateStoreName`). On the next run for the same company it fills: - `previous_open_jobs_total` — the count from the last run. - `open_jobs_change` — current minus previous. - `open_jobs_change_label` — `increased` / `decreased` / `unchanged` / `first_seen`. The snapshot is only updated **after** a company row is successfully saved and charged. Use the same `stateStoreName` across scheduled runs to build a simple hiring trend per company. *** ### 💰 Pricing **Pay-Per-Event**. One flat event per saved company row (final per-event price is configured on the Apify console): | Event | Charged when | | ---------------- | -------------------------------------------------------------------------------------------------- | | `company-result` | Once per valid, unique company row that passed the `minOpenJobs` filter and was saved to the data. | So your bill is simply `results_saved × price_per_event`. The actor honors the user-configured per-run spending cap (Apify `eventChargeLimitReached`): it caps how many companies it resolves up-front to what the limit can pay for, and stops cleanly the moment the cap is reached. **Not charged**: duplicate companies, failed inputs (e.g. an unresolvable name), companies filtered out by `minOpenJobs`, and failed/blocked requests. #### 🚦 Proxy policy Use **Apify Datacenter** proxy or **no proxy** for normal runs — both work for LinkedIn's public company/jobs surface at this actor's conservative concurrency. **Apify Residential proxy is not supported.** The actor will fail at startup if `proxyConfiguration.apifyProxyGroups` includes `RESIDENTIAL`. Reason: in pay-per-event actors, residential bandwidth (~/GB) is billed to the developer, not the run user, so a single bandwidth-heavy run could exceed the per-result event revenue. If you genuinely need residential routing, supply your own residential provider via the proxy editor's **Custom proxy URLs** field — that traffic goes through your provider, not Apify, and is unaffected: ``` http://user:pass@proxy.iproyal.com:12321 http://user:pass@proxy.brightdata.com:22225 http://user:pass@proxy.oxylabs.io:7777 ``` *** ### 📊 Run summary After each run, a `RUN_SUMMARY` entry is written to the key-value store (with `FAILED_INPUTS` when any input could not be resolved): ```json { "actor_name": "LinkedIn Company Hiring Tracker", "inputs_total": 25, "company_urls_total": 20, "company_names_total": 5, "companies_after_deduplication": 23, "successful_companies": 20, "partial_companies": 2, "failed_companies": 1, "raw_jobs_found": 1840, "jobs_scanned": 950, "results_saved": 22, "duplicates_removed": 2, "filtered_out": 1, "charged_events": 22, "blocked_requests": 3, "retry_count": 8, "change_tracking_enabled": true, "state_store_name": "linkedin-company-hiring-tracker-state", "runtime_seconds": 312, "scraped_at": "2026-05-25T00:00:00.000Z" } ``` `charged_events` equals the number of successfully saved company rows. *** ### ⚙️ Filters & limits | Setting | Effect | | ---------------------- | --------------------------------------------------------------------------------------------------- | | `maxCompanies` | Stops processing new companies once reached (1–1000). | | `maxJobsPerCompany` | Stops scanning a company's jobs once reached; sets `jobs_scan_limited` + `scan_limited` tag. | | `postedDate` | `any` / `past24h` / `past7d` / `past30d`. Applied at the LinkedIn source where available. | | `minOpenJobs` | Save only companies with at least this many open jobs. Filtered companies are not saved or charged. | | `deduplicateCompanies` | Process each company once (by ID → URL → slug → name). | *** ### 🚧 Limitations (V1) - **Public guest data only**: no login, cookies, or member-only content. Some company metadata (`company_id`, `company_industry`, `company_size`, `company_headquarters`) is only filled when LinkedIn exposes it publicly; otherwise it falls back to `null` and the company's jobs are still tracked. - **Worldwide scope**: jobs are counted across LinkedIn's global "Worldwide" listing so a company's full open-role footprint is captured regardless of where the run executes. - **Workplace mix is best-effort**: LinkedIn's public job *cards* do not expose a remote/hybrid flag, so `remote_jobs_count` / `hybrid_jobs_count` are only set when a job's title or location text says so. Otherwise a located role is counted as `onsite_jobs_count` (per the on-site fallback). Precise remote/hybrid splits would require visiting each job's detail page, which V1 avoids for cost/speed. - **Company-level output**: one row per company. There is no per-job dataset in V1 (sample jobs are flat fields only). - **`open_jobs_total`** reflects the unique public jobs visible during the run, up to `maxJobsPerCompany`. - **Ambiguous company names** resolve to whichever company owns that exact LinkedIn slug (e.g. `csg` → the company at `/company/csg/`), which may not be the one you intended. For precise targeting, use `companyUrls`. - **Company-name resolution** is best-effort. Names that cannot be resolved to a public company are reported in `FAILED_INPUTS` and are not charged. - **No** recruiter/contact extraction, email enrichment, website crawling, salary parsing, or AI scoring. - LinkedIn guest pagination tops out around ~1,000 jobs per company. *** ### ❓ FAQ **Do I need a LinkedIn account or cookies?** No. The actor only uses LinkedIn's public company and guest jobs surfaces. **Can I track companies by name instead of URL?** Yes — put them in `companyNames`. The actor resolves them best-effort to a public company; unresolved names land in `FAILED_INPUTS`. URLs are more reliable. **How does change tracking work across scheduled runs?** Keep `includeChangeTracking: true` and reuse the same `stateStoreName`. Each run compares to the previous snapshot and fills `open_jobs_change` / `open_jobs_change_label`. **How is `open_jobs_total` counted?** It's the number of unique public jobs found for the company during the run, capped by `maxJobsPerCompany` (when capped, `jobs_scan_limited` is `true`). **Can I export to CSV?** Yes — every field is flat (no nested objects). Use Apify's CSV / Excel export, or call the dataset API with `format=csv`. **Will I get blocked?** The actor uses conservative concurrency, realistic headers, session rotation, and retry/backoff. Default Apify Proxy is sufficient for typical runs. If one company is blocked it's marked partial/failed and the run continues. *** ### 🛠️ Technical notes - **Stack**: Node.js 22 · Apify SDK 3 · Crawlee `CheerioCrawler` · Cheerio + native fetch. No browser. - **Surfaces**: LinkedIn public company page (metadata + numeric org id) and the guest `seeMoreJobPostings` jobs search scoped per company. - **Concurrency**: `min=1`, `max=5` (conservative; tune after real runs). - **Memory**: 1 GB min · 2 GB default · 4 GB max. - **Proxy**: Apify Proxy enabled by default; custom configs accepted; Apify Residential rejected at startup. # Actor input Schema ## `companyUrls` (type: `array`): Primary input. LinkedIn company URLs to track, for example "https://www.linkedin.com/company/atlassian/". Provide at least one of Company LinkedIn URLs or Company names. ## `companyNames` (type: `array`): Convenience input. Plain company names the actor will try to resolve to a public LinkedIn company. Names that cannot be resolved are reported in FAILED\_INPUTS. ## `maxCompanies` (type: `integer`): Maximum number of companies processed in this run. Range 1-1000. ## `maxJobsPerCompany` (type: `integer`): Maximum number of job cards scanned per company before stopping (sets jobs\_scan\_limited). Controls cost and runtime. Range 1-1000. ## `postedDate` (type: `string`): Only consider jobs posted within this window, applied at the LinkedIn source where possible. ## `includeJobSamples` (type: `boolean`): Add up to 3 sample job titles and URLs as flat fields per company. Does not switch to per-job output and does not affect counts or scoring. ## `includeChangeTracking` (type: `boolean`): Compare each company's current open-jobs count against the previous run stored in a named key-value store, and fill previous\_open\_jobs\_total / open\_jobs\_change / open\_jobs\_change\_label. Ideal for scheduled runs. ## `stateStoreName` (type: `string`): Name of the Apify named key-value store holding per-company snapshots between runs. Used only when change tracking is enabled. ## `minOpenJobs` (type: `integer`): Save only companies with at least this many open jobs. Applied after aggregation; filtered companies are not saved or charged. Range 0-10000. ## `deduplicateCompanies` (type: `boolean`): Skip repeated companies so each is processed and charged once (by company ID, then URL, then slug, then name). ## `proxyConfiguration` (type: `object`): Apify Proxy configuration. Defaults to Apify Proxy enabled. Apify Residential is NOT supported and will fail the run at startup; if you need residential routing, supply your own provider via Custom proxy URLs (proxyUrls). ## Actor input object example ```json { "companyUrls": [ "https://www.linkedin.com/company/atlassian/", "https://www.linkedin.com/company/canva/" ], "companyNames": [], "maxCompanies": 100, "maxJobsPerCompany": 250, "postedDate": "any", "includeJobSamples": true, "includeChangeTracking": true, "stateStoreName": "linkedin-company-hiring-tracker-state", "minOpenJobs": 0, "deduplicateCompanies": true, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `overview` (type: `string`): Flat table view with one row per company: identity, open-roles counts, top functions/locations, seniority and remote/hybrid mix, change since last run, and the derived hiring-signal score, label, and reason tags. # 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 = { "companyUrls": [ "https://www.linkedin.com/company/atlassian/", "https://www.linkedin.com/company/canva/" ], "companyNames": [], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("coregent/linkedin-company-hiring-tracker").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 = { "companyUrls": [ "https://www.linkedin.com/company/atlassian/", "https://www.linkedin.com/company/canva/", ], "companyNames": [], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("coregent/linkedin-company-hiring-tracker").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 '{ "companyUrls": [ "https://www.linkedin.com/company/atlassian/", "https://www.linkedin.com/company/canva/" ], "companyNames": [], "proxyConfiguration": { "useApifyProxy": true } }' | apify call coregent/linkedin-company-hiring-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=coregent/linkedin-company-hiring-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Company Hiring Tracker", "description": "Track open LinkedIn jobs for a list of companies and get one clean hiring-signal row per company - open roles, top functions, locations, seniority mix, remote/hybrid count, and change since last run. No LinkedIn login or cookies.", "version": "1.0", "x-build-id": "e9anuHibMcsdenboU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/coregent~linkedin-company-hiring-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-coregent-linkedin-company-hiring-tracker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/coregent~linkedin-company-hiring-tracker/runs": { "post": { "operationId": "runs-sync-coregent-linkedin-company-hiring-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/coregent~linkedin-company-hiring-tracker/run-sync": { "post": { "operationId": "run-sync-coregent-linkedin-company-hiring-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "companyUrls": { "title": "Company LinkedIn URLs", "type": "array", "description": "Primary input. LinkedIn company URLs to track, for example \"https://www.linkedin.com/company/atlassian/\". Provide at least one of Company LinkedIn URLs or Company names.", "default": [], "items": { "type": "string" } }, "companyNames": { "title": "Company names", "type": "array", "description": "Convenience input. Plain company names the actor will try to resolve to a public LinkedIn company. Names that cannot be resolved are reported in FAILED_INPUTS.", "default": [], "items": { "type": "string" } }, "maxCompanies": { "title": "Max companies", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of companies processed in this run. Range 1-1000.", "default": 100 }, "maxJobsPerCompany": { "title": "Max jobs per company", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of job cards scanned per company before stopping (sets jobs_scan_limited). Controls cost and runtime. Range 1-1000.", "default": 250 }, "postedDate": { "title": "Posted date", "enum": [ "any", "past24h", "past7d", "past30d" ], "type": "string", "description": "Only consider jobs posted within this window, applied at the LinkedIn source where possible.", "default": "any" }, "includeJobSamples": { "title": "Include sample jobs", "type": "boolean", "description": "Add up to 3 sample job titles and URLs as flat fields per company. Does not switch to per-job output and does not affect counts or scoring.", "default": true }, "includeChangeTracking": { "title": "Track change since last run", "type": "boolean", "description": "Compare each company's current open-jobs count against the previous run stored in a named key-value store, and fill previous_open_jobs_total / open_jobs_change / open_jobs_change_label. Ideal for scheduled runs.", "default": true }, "stateStoreName": { "title": "Change-tracking store name", "type": "string", "description": "Name of the Apify named key-value store holding per-company snapshots between runs. Used only when change tracking is enabled.", "default": "linkedin-company-hiring-tracker-state" }, "minOpenJobs": { "title": "Minimum open jobs", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Save only companies with at least this many open jobs. Applied after aggregation; filtered companies are not saved or charged. Range 0-10000.", "default": 0 }, "deduplicateCompanies": { "title": "Deduplicate companies", "type": "boolean", "description": "Skip repeated companies so each is processed and charged once (by company ID, then URL, then slug, then name).", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy configuration. Defaults to Apify Proxy enabled. Apify Residential is NOT supported and will fail the run at startup; if you need residential routing, supply your own provider via Custom proxy URLs (proxyUrls).", "default": { "useApifyProxy": 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 } } } } } } } } } } ```