# Greenhouse ATS Job Scraper Pro (`maverickpoint/greenhouse-ats-scraper`) Actor Extract and enrich jobs from 7,500+ Greenhouse companies. Skills extraction, job classification, change detection, deduplication, salary estimation, and hiring analytics. 150+ company registry. No API key needed. - **URL**: https://apify.com/maverickpoint/greenhouse-ats-scraper.md - **Developed by:** [Rahul Sharma](https://apify.com/maverickpoint) (community) - **Categories:** Jobs, Lead generation - **Stats:** 5 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 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 ## Greenhouse ATS Job Scraper Pro The most intelligent Greenhouse job scraper on Apify. Don't just extract jobs — **understand them**. Every competitor gives you raw API data. This scraper gives you **enriched, classified, deduplicated data** with change tracking, skills extraction, salary estimation, and hiring analytics. Built for recruiters, aggregators, and HR analytics teams who need structured intelligence, not raw JSON dumps. **No API key needed.** Greenhouse job board data is publicly accessible via their REST API. ### What makes this different? | Feature | Other Scrapers | This Scraper | |---|---|---| | Job extraction | Yes | Yes | | Skills extraction (required vs preferred) | No | **500-term taxonomy** | | Seniority classification | No | **intern to c-level** | | Job category standardization | No | **13 categories** | | Work mode detection | No | **remote/hybrid/onsite** | | Change detection between runs | No | **new/updated/removed** | | Cross-board deduplication | No | **fingerprint matching** | | Salary estimation for missing data | No | **peer-based with confidence** | | Per-company hiring analytics | No | **department/skill/salary breakdowns** | | Company discovery by name/industry | No | **150+ company registry** | | Output profiles (full/compact/minimal) | No | **3 profiles** | ### What data do you get? #### Core fields (every job) - **Job title, ID, internal job ID, requisition ID** - **Company name and board token** - **Location** (city, state, remote, etc.) - **Departments** and **Offices** - **Salary / pay ranges** (where companies publish pay transparency data) - **Full job description** (HTML + clean text) - **Application URL** (direct link to apply) - **Application questions** (optional) - **Last updated date** #### Enrichment fields (opt-in) - **`seniority`**: `intern`, `entry`, `mid`, `senior`, `staff`, `principal`, `lead`, `manager`, `director`, `vp`, `c-level` - **`category`**: `engineering`, `design`, `product`, `marketing`, `sales`, `customer-success`, `operations`, `hr`, `finance`, `legal`, `data`, `devops`, `security` - **`workMode`**: `remote`, `hybrid`, `onsite`, `unknown` - **`skills`**: `{ required: ["Python", "AWS"], preferred: ["Kubernetes"], yearsExperience: "5+" }` - **`changeStatus`**: `new`, `updated`, `removed`, `unchanged` - **`estimatedSalary`**: `{ min, max, currency, confidence, basedOn, disclaimer }` - **`isDuplicate`** / **`duplicateOf`**: Cross-board duplicate detection ### Who uses Greenhouse? Over 7,500 companies including Airbnb, Stripe, Figma, Webflow, HubSpot, Datadog, Coinbase, Discord, Spotify, Pinterest, and thousands more. If a company's career page URL contains `greenhouse.io`, this scraper works. ### How to use #### Option 1: Board tokens (you know the companies) ```json { "boardTokens": ["webflow", "figma", "stripe", "airbnb"], "enableClassification": true, "enableSkillsExtraction": true } ```` #### Option 2: Search by company name ```json { "companySearch": "Stripe", "enableClassification": true } ``` #### Option 3: Scrape an entire industry ```json { "industryFilter": "fintech", "enableClassification": true, "enableSkillsExtraction": true, "includeAnalytics": true } ``` #### Option 4: Monitor hiring changes (repeat runs) ```json { "boardTokens": ["stripe", "figma", "airbnb"], "enableChangeDetection": true, "deltaOnly": true } ``` Set this on a daily schedule. On repeat runs, only new, updated, and removed jobs are returned — saving 85-95% on costs. ### Output examples #### Standard job record (with classification) ```json { "jobId": 127817, "title": "Senior Backend Engineer", "company": "Webflow", "boardToken": "webflow", "location": "San Francisco, CA (Hybrid)", "departments": ["Engineering"], "offices": ["San Francisco"], "applyUrl": "https://boards.greenhouse.io/webflow/jobs/127817", "updatedAt": "2026-03-28T10:55:28-05:00", "seniority": "senior", "category": "engineering", "workMode": "hybrid", "payRanges": [ { "title": "Base Salary", "minValue": "150000", "maxValue": "200000", "currency": "USD", "interval": "yearly" } ], "descriptionText": "We are looking for a Senior Backend Engineer...", "scrapedAt": "2026-04-01T12:00:00.000Z", "source": "greenhouse" } ``` #### With skills extraction ```json { "jobId": 127817, "title": "Senior Backend Engineer", "company": "Webflow", "skills": { "required": ["Python", "Node.js", "PostgreSQL", "AWS", "Docker", "REST API"], "preferred": ["Kubernetes", "GraphQL", "Terraform"], "allSkills": [ { "name": "Python", "category": "language", "context": "required" }, { "name": "Kubernetes", "category": "cloud", "context": "preferred" } ], "yearsExperience": "5+" } } ``` #### Analytics summary (per company) ```json { "type": "analytics", "company": "Stripe", "boardToken": "stripe", "totalJobs": 495, "departmentBreakdown": [ { "name": "Engineering", "count": 180 }, { "name": "Sales", "count": 95 } ], "seniorityBreakdown": [ { "name": "senior", "count": 210 }, { "name": "mid", "count": 150 } ], "workModeBreakdown": [ { "name": "onsite", "count": 300 }, { "name": "hybrid", "count": 120 }, { "name": "remote", "count": 75 } ], "topSkills": [ { "name": "Python", "count": 85 }, { "name": "SQL", "count": 72 }, { "name": "AWS", "count": 65 } ], "salaryStats": { "jobsWithSalary": 120, "jobsWithoutSalary": 375, "salaryCoveragePercent": 24 } } ``` ### Input reference #### Company Selection | Field | Type | Default | Description | |---|---|---|---| | `boardTokens` | string\[] | `[]` | Greenhouse board tokens or full URLs | | `companySearch` | string | `""` | Search 150+ company registry by name | | `industryFilter` | string | `""` | Filter registry by industry (saas, fintech, ai, etc.) | #### Data Options | Field | Type | Default | Description | |---|---|---|---| | `includeDescription` | boolean | `true` | Include HTML + text job descriptions | | `includeQuestions` | boolean | `false` | Include application form questions | | `departmentFilter` | string | `""` | Filter by department (partial match) | | `locationFilter` | string | `""` | Filter by location (partial match) | | `maxJobsPerCompany` | integer | `0` | Limit per company (0 = unlimited) | #### Enrichment | Field | Type | Default | Description | |---|---|---|---| | `enableClassification` | boolean | `true` | Seniority, category, work mode | | `enableSkillsExtraction` | boolean | `false` | Required/preferred skills + years | | `enableSalaryEstimation` | boolean | `false` | Peer-based salary estimation | #### Tracking | Field | Type | Default | Description | |---|---|---|---| | `enableChangeDetection` | boolean | `false` | Track new/updated/removed between runs | | `deltaOnly` | boolean | `false` | Only output changes (skip unchanged) | | `deduplicateAcrossBoards` | boolean | `false` | Flag cross-board duplicates | #### Output | Field | Type | Default | Description | |---|---|---|---| | `includeAnalytics` | boolean | `false` | Per-company hiring analytics summary | | `outputProfile` | enum | `"full"` | `full` / `compact` / `minimal` | ### Finding board tokens Not sure what a company's board token is? Three options: 1. **Use company search**: Just type the company name in `companySearch` — we'll find it 2. **Check their careers page**: Look for URLs containing `greenhouse.io`. The token is the path after the domain: `https://boards.greenhouse.io/webflow` -> `webflow` 3. **Google it**: Search `site:boards.greenhouse.io [company name]` ### Use cases - **Recruitment agencies**: Monitor job openings across target companies with change detection - **Job aggregators**: Feed classified, deduplicated listings into your job board - **Salary benchmarking**: Collect pay range data + peer-based estimates across industries - **Competitive intelligence**: Track which roles competitors are hiring, what skills they need, and how fast they're growing - **HR analytics**: Analyze hiring trends with per-company analytics summaries - **AI/LLM data pipelines**: Feed structured, enriched job data into RAG systems ### Pricing **Pay Per Result: $2 per 1,000 jobs** ($0.002 per job). With the Apify Free plan ($5/month in credits), extract ~2,500 jobs/month free. **Cost-saving tip**: Use `enableChangeDetection` + `deltaOnly` on scheduled runs. After the first full scrape, subsequent runs only return changes — cutting costs by 85-95%. ### API access ```bash curl "https://api.apify.com/v2/acts/YOUR_USERNAME~greenhouse-ats-scraper/runs" \ -X POST \ -H "Content-Type: application/json" \ -H "Authorization: Bearer YOUR_API_TOKEN" \ -d '{ "boardTokens": ["webflow", "stripe"], "enableClassification": true, "enableSkillsExtraction": true, "includeAnalytics": true }' ``` ### Related scrapers Looking for other ATS platforms? Check out our suite: - **Lever Job Scraper** (coming soon) - **Ashby Job Scraper** (coming soon) ### Feedback Found a bug or have a feature request? Open an issue on the **Issues** tab. # Actor input Schema ## `boardTokens` (type: `array`): List of Greenhouse board tokens (the company slug from their careers URL). Example: 'webflow' from https://boards.greenhouse.io/webflow. You can also paste full URLs. ## `companySearch` (type: `string`): Search the built-in registry of 200+ companies by name. If not found in the registry, auto-discovers the token by trying common patterns. ## `industryFilter` (type: `string`): Load all companies from a specific industry. Options: saas, fintech, healthtech, ecommerce, cybersecurity, devtools, data, ai, enterprise, edtech, media, gaming, crypto, hr, logistics, biotech, etc. ## `includeDescription` (type: `boolean`): Include the full HTML and plain-text job description. Increases data size but required for skills extraction. ## `includeQuestions` (type: `boolean`): Include the application form questions for each job post (label, required, type). ## `departmentFilter` (type: `string`): Only return jobs matching this department name (case-insensitive partial match). Leave empty for all. ## `locationFilter` (type: `string`): Only return jobs matching this location string (case-insensitive partial match). Leave empty for all. ## `maxJobsPerCompany` (type: `integer`): Maximum number of jobs to extract per company. Set to 0 for unlimited. ## `enableClassification` (type: `boolean`): Add seniority level (intern→c-level), standardized category (engineering, design, sales, etc.), and work mode (remote/hybrid/onsite) to each job. ## `enableSkillsExtraction` (type: `boolean`): Parse job descriptions to extract required vs. preferred skills, technologies, and years of experience. Uses a 500-term taxonomy covering languages, frameworks, tools, cloud, data/ML, and more. ## `enableSalaryEstimation` (type: `boolean`): For jobs without pay data, estimate salary ranges based on similar roles in this scrape run. Clearly labeled with confidence level and disclaimer. Requires classification to be enabled. ## `enableChangeDetection` (type: `boolean`): Compare with previous run to mark each job as new, updated, removed, or unchanged. Uses Apify KeyValueStore for persistence across runs. ## `deltaOnly` (type: `boolean`): When change detection is enabled, only output new, updated, and removed jobs — skip unchanged ones. Saves 85-95% on repeat runs. ## `deduplicateAcrossBoards` (type: `boolean`): Detect and flag duplicate jobs posted across multiple company boards (e.g., parent company + subsidiary). Uses Greenhouse internal job ID as fingerprint. ## `includeAnalytics` (type: `boolean`): Add a per-company analytics summary: department/location/seniority/work-mode breakdowns, top skills, salary coverage stats, and change counts. ## `outputProfile` (type: `string`): Control output detail level. Full: all fields including HTML descriptions. Compact: core fields + enrichments, no HTML. Minimal: ID, title, company, location, apply URL only. ## Actor input object example ```json { "boardTokens": [ "webflow", "figma", "notion" ], "companySearch": "", "industryFilter": "", "includeDescription": true, "includeQuestions": false, "departmentFilter": "", "locationFilter": "", "maxJobsPerCompany": 0, "enableClassification": true, "enableSkillsExtraction": false, "enableSalaryEstimation": false, "enableChangeDetection": false, "deltaOnly": false, "deduplicateAcrossBoards": false, "includeAnalytics": false, "outputProfile": "full" } ``` # 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 = { "boardTokens": [ "webflow", "figma", "notion" ] }; // Run the Actor and wait for it to finish const run = await client.actor("maverickpoint/greenhouse-ats-scraper").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 = { "boardTokens": [ "webflow", "figma", "notion", ] } # Run the Actor and wait for it to finish run = client.actor("maverickpoint/greenhouse-ats-scraper").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 '{ "boardTokens": [ "webflow", "figma", "notion" ] }' | apify call maverickpoint/greenhouse-ats-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=maverickpoint/greenhouse-ats-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Greenhouse ATS Job Scraper Pro", "description": "Extract and enrich jobs from 7,500+ Greenhouse companies. Skills extraction, job classification, change detection, deduplication, salary estimation, and hiring analytics. 150+ company registry. No API key needed.", "version": "2.0", "x-build-id": "yfOLJgCkfeDIWbIKj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/maverickpoint~greenhouse-ats-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-maverickpoint-greenhouse-ats-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/maverickpoint~greenhouse-ats-scraper/runs": { "post": { "operationId": "runs-sync-maverickpoint-greenhouse-ats-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/maverickpoint~greenhouse-ats-scraper/run-sync": { "post": { "operationId": "run-sync-maverickpoint-greenhouse-ats-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "boardTokens": { "title": "Company Board Tokens", "type": "array", "description": "List of Greenhouse board tokens (the company slug from their careers URL). Example: 'webflow' from https://boards.greenhouse.io/webflow. You can also paste full URLs.", "items": { "type": "string" } }, "companySearch": { "title": "Search Company by Name", "type": "string", "description": "Search the built-in registry of 200+ companies by name. If not found in the registry, auto-discovers the token by trying common patterns.", "default": "" }, "industryFilter": { "title": "Filter by Industry", "type": "string", "description": "Load all companies from a specific industry. Options: saas, fintech, healthtech, ecommerce, cybersecurity, devtools, data, ai, enterprise, edtech, media, gaming, crypto, hr, logistics, biotech, etc.", "default": "" }, "includeDescription": { "title": "Include Full Job Description", "type": "boolean", "description": "Include the full HTML and plain-text job description. Increases data size but required for skills extraction.", "default": true }, "includeQuestions": { "title": "Include Application Questions", "type": "boolean", "description": "Include the application form questions for each job post (label, required, type).", "default": false }, "departmentFilter": { "title": "Filter by Department", "type": "string", "description": "Only return jobs matching this department name (case-insensitive partial match). Leave empty for all.", "default": "" }, "locationFilter": { "title": "Filter by Location", "type": "string", "description": "Only return jobs matching this location string (case-insensitive partial match). Leave empty for all.", "default": "" }, "maxJobsPerCompany": { "title": "Max Jobs Per Company", "minimum": 0, "type": "integer", "description": "Maximum number of jobs to extract per company. Set to 0 for unlimited.", "default": 0 }, "enableClassification": { "title": "Auto-Classify Jobs", "type": "boolean", "description": "Add seniority level (intern→c-level), standardized category (engineering, design, sales, etc.), and work mode (remote/hybrid/onsite) to each job.", "default": true }, "enableSkillsExtraction": { "title": "Extract Skills & Technologies", "type": "boolean", "description": "Parse job descriptions to extract required vs. preferred skills, technologies, and years of experience. Uses a 500-term taxonomy covering languages, frameworks, tools, cloud, data/ML, and more.", "default": false }, "enableSalaryEstimation": { "title": "Estimate Missing Salaries", "type": "boolean", "description": "For jobs without pay data, estimate salary ranges based on similar roles in this scrape run. Clearly labeled with confidence level and disclaimer. Requires classification to be enabled.", "default": false }, "enableChangeDetection": { "title": "Track Changes Between Runs", "type": "boolean", "description": "Compare with previous run to mark each job as new, updated, removed, or unchanged. Uses Apify KeyValueStore for persistence across runs.", "default": false }, "deltaOnly": { "title": "Delta Only (Changes Only)", "type": "boolean", "description": "When change detection is enabled, only output new, updated, and removed jobs — skip unchanged ones. Saves 85-95% on repeat runs.", "default": false }, "deduplicateAcrossBoards": { "title": "Deduplicate Across Boards", "type": "boolean", "description": "Detect and flag duplicate jobs posted across multiple company boards (e.g., parent company + subsidiary). Uses Greenhouse internal job ID as fingerprint.", "default": false }, "includeAnalytics": { "title": "Include Board Analytics", "type": "boolean", "description": "Add a per-company analytics summary: department/location/seniority/work-mode breakdowns, top skills, salary coverage stats, and change counts.", "default": false }, "outputProfile": { "title": "Output Profile", "enum": [ "full", "compact", "minimal" ], "type": "string", "description": "Control output detail level. Full: all fields including HTML descriptions. Compact: core fields + enrichments, no HTML. Minimal: ID, title, company, location, apply URL only.", "default": "full" } } }, "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 } } } } } } } } } } ```