# US Pay-Transparency Compliance Checker for Job Postings (`mahender_sam/pay-transparency-checker`) Actor Check job postings against US state pay-transparency laws. Covers CA, NY, CO, WA, MA, IL, NJ, OR, plus Maine LD 54 (effective 2026-07-29). Returns per-state pass/fail with specific violations. - **URL**: https://apify.com/mahender\_sam/pay-transparency-checker.md - **Developed by:** [Mahender Samperboyina](https://apify.com/mahender_sam) (community) - **Categories:** Jobs, Developer tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## US Pay-Transparency Compliance Checker [![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://python.org) [![Tests](https://img.shields.io/badge/tests-41%20passing-success.svg)]() [![Source](https://img.shields.io/badge/source-MIT-green.svg)](https://github.com/Mahender22/pay-transparency-apify) **Pair this with any job-scraper actor.** Scrape postings from LinkedIn, Indeed, Glassdoor, or company career pages, then feed the results here to flag which postings violate US state pay-transparency laws. Covers **9 states** including Maine LD 54 (effective 2026-07-29) — CA, NY, CO, WA, MA, IL, NJ, OR, ME. You get per-(posting × state) reports with the exact violation text, regulatory notes, and effective-date awareness. ATSes, recruiters, market-research teams, and comp analysts use it as the compliance layer on top of their existing scraping pipeline. --- ### Works seamlessly with Run any of these scrapers first, then chain their dataset into this actor: - [misceres/indeed-scraper](https://apify.com/misceres/indeed-scraper) — Indeed job postings - [curious_coder/indeed-scraper](https://apify.com/curious_coder/indeed-scraper) — alternate Indeed scraper with employer details - [bebity/linkedin-jobs-scraper](https://apify.com/bebity/linkedin-jobs-scraper) — LinkedIn job listings - [bebity/glassdoor-jobs-scraper](https://apify.com/bebity/glassdoor-jobs-scraper) — Glassdoor postings - Or any other actor that returns job-posting JSON The expected input shape is documented below. If the scraper's field names differ from ours, a one-step transform (Apify Tasks or webhook) maps `jobTitle → title`, `salaryMin → salary_min`, etc. --- ### What gets checked For each (posting, state) pair: - **Numeric salary range present** (CA, NY, CO, WA, MA, IL, OR, ME require it; NJ is on-request only) - **Range plausibility** (inverted min > max; ≥10× spread flagged as bad-faith disclosure) - **No vague-pay phrases** alongside the range ("competitive", "DOE", "negotiable") — several state DOLs flag these as non-compliant - **Benefits description present** (CO, WA, IL require it) - **Employer size threshold** (e.g. CA 15+, MA 25+; smaller employers exempt) - **Effective-date awareness** (Maine LD 54 returns soft-pass before 2026-07-29 with a clear note) ### Input ```json { "postings": [ { "title": "Senior Software Engineer", "description": "We are hiring a senior engineer.", "salary_min": 140000, "salary_max": 180000, "benefits": "Medical, dental, vision, 401k 4% match.", "employer_size": 250 } ], "states": ["CA", "CO", "NY", "WA"] } ```` `employer_size` is optional — when omitted, the checker assumes the posting is from an employer above the threshold (most postings are from larger companies). For small-employer accuracy, fill it in. ### Output (one dataset item per posting × state) A compliant posting: ```json { "posting_title": "Senior Software Engineer", "state": "CA", "passes": true, "violations": [], "notes": [], "rule_effective": true } ``` A non-compliant posting (Colorado requires both salary AND benefits): ```json { "posting_title": "Marketing Manager", "state": "CO", "passes": false, "violations": [ "Colorado requires a numeric salary range in the posting (found min=None, max=None).", "Colorado requires a benefits description in the posting." ], "notes": ["Applies to remote jobs that could be performed in CO."], "rule_effective": true } ``` ### Pricing Currently **free**. You only pay Apify's standard platform compute (typically a fraction of a cent per posting checked). Per-result creator pricing arrives once usage proves demand. ### Local development ```bash python -m venv .venv ## Windows: .venv\Scripts\activate ## Mac/Linux: source .venv/bin/activate pip install -e ".[dev]" pytest ## 41 tests, ~50ms python main.py --local ## run the entrypoint without Apify SDK ``` ### Sister projects This actor shares its compliance rule data with two other surfaces of the same product: - [hr-compliance-mcp](https://github.com/Mahender22/hr-compliance-mcp) — open-source MCP server for Claude / Cursor / Windsurf. 19 tools covering wage, overtime, leave, transparency, discrimination, and more across the same 9 states. - [hr-compliance-site](https://github.com/Mahender22/hr-compliance-site) — interactive demo + REST API waitlist for teams that need HTTP access without MCP. ### License [MIT](LICENSE) — source at [github.com/Mahender22/pay-transparency-apify](https://github.com/Mahender22/pay-transparency-apify). # Actor input Schema ## `postings` (type: `array`): Array of job-posting objects. Each item should include title, description, salary\_min/max, benefits, and employer\_size where known. ## `states` (type: `array`): Two-letter US state codes. Currently supported: CA, NY, CO, WA, MA, IL, NJ, OR, ME. ## Actor input object example ```json { "postings": [ { "title": "Senior Software Engineer", "description": "We are hiring a senior engineer to join our platform team.", "salary_min": 140000, "salary_max": 180000, "benefits": "Medical, dental, vision, 401k 4% match, unlimited PTO.", "employer_size": 250 }, { "title": "Marketing Manager", "description": "Competitive salary based on experience.", "salary_min": null, "salary_max": null, "benefits": null, "employer_size": 80 } ], "states": [ "CA", "CO", "NY", "WA" ] } ``` # 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 = { "postings": [ { "title": "Senior Software Engineer", "description": "We are hiring a senior engineer to join our platform team.", "salary_min": 140000, "salary_max": 180000, "benefits": "Medical, dental, vision, 401k 4% match, unlimited PTO.", "employer_size": 250 }, { "title": "Marketing Manager", "description": "Competitive salary based on experience.", "salary_min": null, "salary_max": null, "benefits": null, "employer_size": 80 } ], "states": [ "CA", "CO", "NY", "WA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("mahender_sam/pay-transparency-checker").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 = { "postings": [ { "title": "Senior Software Engineer", "description": "We are hiring a senior engineer to join our platform team.", "salary_min": 140000, "salary_max": 180000, "benefits": "Medical, dental, vision, 401k 4% match, unlimited PTO.", "employer_size": 250, }, { "title": "Marketing Manager", "description": "Competitive salary based on experience.", "salary_min": None, "salary_max": None, "benefits": None, "employer_size": 80, }, ], "states": [ "CA", "CO", "NY", "WA", ], } # Run the Actor and wait for it to finish run = client.actor("mahender_sam/pay-transparency-checker").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 '{ "postings": [ { "title": "Senior Software Engineer", "description": "We are hiring a senior engineer to join our platform team.", "salary_min": 140000, "salary_max": 180000, "benefits": "Medical, dental, vision, 401k 4% match, unlimited PTO.", "employer_size": 250 }, { "title": "Marketing Manager", "description": "Competitive salary based on experience.", "salary_min": null, "salary_max": null, "benefits": null, "employer_size": 80 } ], "states": [ "CA", "CO", "NY", "WA" ] }' | apify call mahender_sam/pay-transparency-checker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mahender_sam/pay-transparency-checker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "US Pay-Transparency Compliance Checker for Job Postings", "description": "Check job postings against US state pay-transparency laws. Covers CA, NY, CO, WA, MA, IL, NJ, OR, plus Maine LD 54 (effective 2026-07-29). Returns per-state pass/fail with specific violations.", "version": "0.1", "x-build-id": "1g1XWs0wGMkPrSBGo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mahender_sam~pay-transparency-checker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mahender_sam-pay-transparency-checker", "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/mahender_sam~pay-transparency-checker/runs": { "post": { "operationId": "runs-sync-mahender_sam-pay-transparency-checker", "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/mahender_sam~pay-transparency-checker/run-sync": { "post": { "operationId": "run-sync-mahender_sam-pay-transparency-checker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "postings", "states" ], "properties": { "postings": { "title": "Job postings", "type": "array", "description": "Array of job-posting objects. Each item should include title, description, salary_min/max, benefits, and employer_size where known." }, "states": { "title": "States to check against", "uniqueItems": true, "type": "array", "description": "Two-letter US state codes. Currently supported: CA, NY, CO, WA, MA, IL, NJ, OR, ME.", "items": { "type": "string", "pattern": "^[A-Za-z]{2}$" } } } }, "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 } } } } } } } } } } ```