# LinkedIn Profile Enricher PRO โœ… No Cookies (`atomus/linkedin-profile-enricher`) Actor Enrich LinkedIn profiles with name, title, headline, summary, company, location, skills, education, and work history. Submit up to 5,000 URLs per run, each returns one structured record. Pay only for profiles found, not-found and errors are free. No LinkedIn account or cookies needed. - **URL**: https://apify.com/atomus/linkedin-profile-enricher.md - **Developed by:** [Atomus APIs](https://apify.com/atomus) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 8 total users, 6 monthly users, 95.9% runs succeeded, 3 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $6.00 / 1,000 profile enricheds 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 ## ๐Ÿ” LinkedIn Profile Enricher Enrich any LinkedIn profile URL with structured data: name, job title, headline, summary, company, location, skills, education, and work history. One URL in, one enriched profile out, at scale. **No LinkedIn account or cookies required.** > ๐Ÿ’ก **For other LinkedIn tools by Dende Labs**, check: https://apify.com/dendelabs --- ### โœจ Key Features | Feature | Description | |---------|-------------| | ๐Ÿ“‹ **Rich profile data** | First name, last name, full name, title, headline, summary, picture URL, location, skills, education, and work history. | | ๐ŸŽฏ **Sales / ICP signals** | `open_to_work`, `hiring`, `verified`, `premium` badges; `seniority` (`c_suite`, `vp`, `director`, etc.); department + functions. | | ๐Ÿข **Deeply enriched company** | Legal name, founded year, type, industry, staff count, website, domain, social URLs, full HQ address, tech stack, IPO date, IT spend, and more. | | ๐Ÿ”— **Cross-platform links** | LinkedIn, Twitter / X, GitHub, and Facebook URLs surfaced when discoverable. | | ๐Ÿ’ฐ **Pay only for results** | You are charged **only when a profile is found**. `not_found` and `error` responses are always free. | | ๐Ÿ“ฆ **Batch processing** | Submit up to 5,000 URLs in a single run. | | โšก **1:1 enrichment** | One input URL produces exactly one output record, predictable, easy to join back to your data. | | ๐Ÿ” **No cookies needed** | No LinkedIn account, cookies, or risk of bans. | --- ### ๐Ÿ“ฅ Input #### Basic Usage Just paste one or more LinkedIn profile URLs: ```json { "profileUrls": [ "https://www.linkedin.com/in/satyanadella/" ] } ```` #### All Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `profileUrls` | string\[] | โœ… Yes | (none) | LinkedIn profile URLs. Each must match `https://www.linkedin.com/in//`. Up to 5,000 per run. | #### Supported URL Formats ``` โœ… https://www.linkedin.com/in/satyanadella/ โœ… https://www.linkedin.com/in/satyanadella โœ… https://www.linkedin.com/in/satyanadella/?utm_source=share ``` *** ### ๐Ÿ“ค Output Each input URL produces exactly one record in the dataset. The `status` field tells you what happened: | Status | Charged? | Description | |--------|----------|-------------| | `success` | โœ… Yes ($0.006) | Profile found, full data in the `profile` field. | | `not_found` | โŒ No | Profile not found in the data source (private, deleted, or not indexed). | | `error` | โŒ No | Invalid URL format or upstream network failure. | #### Success Record ```json { "url": "https://www.linkedin.com/in/satyanadella/", "status": "success", "profile": { "identifier": "satyanadella", "first_name": "Satya", "last_name": "Nadella", "full_name": "Satya Nadella", "title": "Chairman and CEO", "headline": "Chairman and CEO at Microsoft", "summary": "As chairman and CEO of Microsoft, I define my mission...", "picture_url": "https://images.ai-ark.com/...", "background_url": "https://media.licdn.com/dms/image/...", "industry": "Computer Software", "location": { "default": "Redmond, Washington, United States, North America", "short": "Redmond, Washington", "country": "United States", "state": "Washington", "city": "Redmond" }, "languages": { "primary_locale": { "country": "US", "language": "en" }, "supported_locales": [{ "country": "US", "language": "en" }] }, "badges": { "premium": true, "creator": true, "open_to_work": false, "hiring": false, "verified": true, "influencer": true }, "department": { "departments": ["c_suite"], "sub_departments": ["founder", "executive"], "functions": ["entrepreneurship"], "seniority": "c_suite" }, "links": { "linkedin": "https://www.linkedin.com/in/satyanadella", "twitter": null, "github": null, "facebook": null }, "skills": [], "educations": [ { "school": { "name": "The University of Chicago Booth School of Business", "logo": "https://images.ai-ark.com/...", "url": "https://www.linkedin.com/school/universityofchicagoboothschoolofbusiness/" }, "date": { "start": "1994-01-01", "end": "1996-12-31" } } ], "position_groups": [ { "company": { "name": "Microsoft", "logo": "https://images.ai-ark.com/...", "url": "https://www.linkedin.com/company/microsoft", "employees": { "start": 10001 } }, "date": { "start": "2014-02-01", "end": null }, "profile_positions": [ { "company": "Microsoft", "title": "Chairman and CEO", "date": { "start": "2014-02-01", "end": null } } ] } ], "company": { "name": "Microsoft", "legal_name": "Microsoft Corporation", "founded_year": 1975, "type": "PUBLIC_COMPANY", "industry": "software development", "staff": { "total": 228018, "range_start": 10001, "range_end": null }, "website": "https://news.microsoft.com", "domain": "microsoft.com", "linkedin_url": "https://www.linkedin.com/company/microsoft", "twitter_url": "https://x.com/Microsoft", "crunchbase_url": "https://www.crunchbase.com/organization/microsoft", "headquarter": { "country": "United States", "state": "Washington", "city": "Redmond", "street": "1 Microsoft Way", "postal_code": "98052", "raw_address": "1 Microsoft Way, Redmond, Washington, United States, North America", "position": { "lng": -122.33279, "lat": 47.591396 } }, "technologies": [{ "name": "organization schema", "category": "framework" }], "industries": ["Software Development"], "keywords": ["AI", "Cloud", "Productivity"], "naics": ["511210"], "revenue_amount": "10000000000-...", "funding_total": 1000000, "ipo_date": "1986-03-13", "it_spend": 66692471976, "last_updated": "2026-04-12" }, "last_updated": "2026-04-12" }, "_metadata": { "extracted_at": "2026-04-28T12:00:00.000Z" } } ``` #### Not Found Record ```json { "url": "https://www.linkedin.com/in/someunknownperson/", "status": "not_found", "_metadata": { "extracted_at": "2026-04-28T12:00:00.000Z" } } ``` #### Error Record ```json { "url": "https://example.com/not-a-linkedin-url", "status": "error", "error_kind": "user_error", "reason": "Invalid LinkedIn profile URL. Expected: https://www.linkedin.com/in//", "_metadata": { "extracted_at": "2026-04-28T12:00:00.000Z" } } ``` #### Output Fields Reference All fields below are nested under `profile` (present when `status = success`). **Identity:** | Field | Type | Description | |-------|------|-------------| | `profile.identifier` | string | null | LinkedIn handle (the slug after `/in/`, e.g. `satyanadella`). | | `profile.first_name` | string | null | First name. | | `profile.last_name` | string | null | Last name. | | `profile.full_name` | string | null | Full display name. | | `profile.title` | string | null | Current job title. | | `profile.headline` | string | null | LinkedIn headline (short tagline under the name). | | `profile.summary` | string | null | About / summary section. | | `profile.picture_url` | string | null | Profile photo URL. | | `profile.background_url` | string | null | Banner / background image URL. | | `profile.birth_date` | string | null | Birth date if exposed by the source. | | `profile.industry` | string | null | Top-level industry classification (e.g. `Computer Software`). | | `profile.last_updated` | string | null | ISO date the upstream source last refreshed this profile. | **Location & locale:** | Field | Type | Description | |-------|------|-------------| | `profile.location.default` | string | Compact one-liner (e.g. `Redmond, Washington, United States, North America`). | | `profile.location.short` | string | Short one-liner (e.g. `Redmond, Washington`). | | `profile.location.country` | string | Country name. | | `profile.location.state` | string | State or region. | | `profile.location.city` | string | City. | | `profile.languages.primary_locale` | object | `{ country, language }` of the profile's primary locale. | | `profile.languages.supported_locales` | object\[] | Other locales the profile is translated into. | **Sales / ICP signals:** | Field | Type | Description | |-------|------|-------------| | `profile.badges.open_to_work` | boolean | True when the profile is flagged Open to Work. | | `profile.badges.hiring` | boolean | True when the profile is hiring. | | `profile.badges.premium` | boolean | LinkedIn Premium subscriber. | | `profile.badges.creator` | boolean | LinkedIn Creator. | | `profile.badges.verified` | boolean | LinkedIn-verified profile. | | `profile.badges.influencer` | boolean | LinkedIn Influencer. | | `profile.department.seniority` | string | null | Seniority level (e.g. `c_suite`, `vp`, `director`, `manager`). | | `profile.department.functions` | string\[] | Functional areas (e.g. `engineering`, `sales`). | | `profile.department.departments` | string\[] | Departments (e.g. `engineering`, `c_suite`). | | `profile.department.sub_departments` | string\[] | Sub-departments. | **Social links:** | Field | Type | Description | |-------|------|-------------| | `profile.links.linkedin` | string | null | Canonical LinkedIn URL from the data source. | | `profile.links.twitter` | string | null | Twitter / X profile URL if discoverable. | | `profile.links.github` | string | null | GitHub profile URL if discoverable. | | `profile.links.facebook` | string | null | Facebook profile URL if discoverable. | **Career history:** | Field | Type | Description | |-------|------|-------------| | `profile.skills` | string\[] | List of skills. | | `profile.educations` | object\[] | Education history. Each entry: `{ school: { id, name, logo, url }, degree_name, field_of_study, grade, date: { start, end } }`. | | `profile.position_groups` | object\[] | Work experience grouped by company. Each entry: `{ company: { id, name, logo, url, employees }, date: { start, end }, profile_positions: [{ company, title, description, employment_type, location, date }] }`. | **Current company (deeply enriched):** | Field | Type | Description | |-------|------|-------------| | `profile.company.name` | string | null | Current company name. | | `profile.company.legal_name` | string | null | Legal company name (e.g. `Microsoft Corporation`). | | `profile.company.description` | string | null | Long-form company description. | | `profile.company.overview` | string | null | Short company overview. | | `profile.company.founded_year` | integer | null | Year founded. | | `profile.company.type` | string | null | `PUBLIC_COMPANY`, `PRIVATELY_HELD`, `NON_PROFIT`, etc. | | `profile.company.industry` | string | null | Company-level industry. | | `profile.company.staff.total` | integer | null | Total employees. | | `profile.company.staff.range_start` | integer | null | Lower bound of employee range. | | `profile.company.website` | string | null | Company website URL. | | `profile.company.domain` | string | null | Root domain (e.g. `microsoft.com`). | | `profile.company.linkedin_url` | string | null | Company LinkedIn page. | | `profile.company.twitter_url` | string | null | Company Twitter / X. | | `profile.company.facebook_url` | string | null | Company Facebook. | | `profile.company.crunchbase_url` | string | null | Company Crunchbase. | | `profile.company.headquarter` | object | null | `{ country, state, city, street, postal_code, raw_address, position: { lng, lat } }`. | | `profile.company.technologies` | object\[] | Tech stack: `[{ name, category }]`. | | `profile.company.industries` | string\[] | Industry tags. | | `profile.company.keywords` | string\[] | SEO / topic keywords. | | `profile.company.naics` | string\[] | NAICS classification codes. | | `profile.company.revenue_amount` | string | null | Revenue range (e.g. `10000000000-...`). | | `profile.company.funding_total` | integer | null | Total funding raised in USD. | | `profile.company.ipo_date` | string | null | IPO date if public. | | `profile.company.it_spend` | integer | null | Estimated annual IT spend in USD (Aberdeen data). Useful for B2B SaaS targeting. | **Provenance:** | Field | Type | Description | |-------|------|-------------| | `_metadata.extracted_at` | string | ISO timestamp of the lookup. | *** ### ๐Ÿ“Œ Examples #### Example 1: Enrich a single profile ```json { "profileUrls": [ "https://www.linkedin.com/in/satyanadella/" ] } ``` #### Example 2: Batch enrichment ```json { "profileUrls": [ "https://www.linkedin.com/in/satyanadella/", "https://www.linkedin.com/in/jeffweiner08/", "https://www.linkedin.com/in/reidhoffman/" ] } ``` Each URL produces its own row in the output dataset. Not-found profiles are included with `status: "not_found"` and are not charged. #### Example 3: Enrich a list from a CRM or spreadsheet Export LinkedIn URLs from your CRM, paste them into `profileUrls`, and run. The output maps 1:1 to your input list by URL, easy to rejoin in any spreadsheet tool or database. *** ### ๐Ÿ’ฐ Pricing This actor uses **pay-per-event** pricing. You are charged **$0.006 per successfully enriched profile** (= $6.00 per 1,000 profiles). #### Free plan limit Apify Free plan users can enrich **up to 20 profiles per calendar month**. The cap resets at the start of each month. To run unlimited enrichments, upgrade to Apify Starter ($49/mo) or higher. Free-tier overflow returns a `status: "error"` record with `error_kind: "free_tier_limit"` and is not charged. **What you are NOT charged for:** - Profiles that returned `not_found` (not in the data source) - Profiles that returned `error` (invalid URL or network failure) - Apify platform compute time (memory/CPU) **Cost examples:** | Profiles enriched | Cost | |-------------------|------| | 100 | $0.60 | | 500 | $3.00 | | 1,000 | $6.00 | | 5,000 | $30.00 | > ๐Ÿ’ก Profiles that aren't found cost nothing, there's no penalty for trying. *** ### ๐Ÿค– Integration with AI Agents This actor is optimized for use with AI agents and LLMs via the Apify MCP server. #### Output Schema Each record has a `status` field (`success` | `not_found` | `error`) and a `profile` object when status is `success`. The profile fields are flat and predictable, ideal for agent post-processing. **Key fields for agents:** - `profile.full_name`: Who this person is - `profile.title` + `profile.headline`: Their current role and self-description - `profile.industry`: Industry classification - `profile.department.seniority`: Seniority level (`c_suite`, `vp`, `director`, etc.) for ICP matching - `profile.badges.open_to_work` / `profile.badges.hiring`: Intent signals - `profile.company.name` + `profile.company.industry` + `profile.company.staff.total`: Where they work, what the company does, headcount - `profile.company.technologies`: Tech stack used by the company - `profile.company.it_spend`: Annual IT spend (B2B SaaS targeting) - `profile.skills`: Areas of expertise - `profile.position_groups`: Career history - `profile.links.{twitter, github, facebook}`: Other social profiles for outreach #### Example Agent Prompt > "Enrich these 10 LinkedIn profiles and summarize each person's role, company, and top 3 skills in a table." The agent can pass the URL list as `profileUrls` and process the structured `profile` output directly, no scraping, no parsing. *** ### ๐ŸŽฏ Use Cases - **๐Ÿ“Š CRM enrichment**: Automatically fill in job title, company, location, and skills for contacts in your CRM - **๐Ÿ”Ž Sales prospecting**: Validate and enrich leads before outreach - **๐Ÿงฉ Recruiting**: Quickly build structured candidate profiles from a list of LinkedIn URLs - **๐Ÿข Account research**: Understand a company's team composition and expertise - **๐Ÿ“‹ Data pipelines**: Feed enriched profile data into downstream tools (Airtable, HubSpot, Salesforce, etc.) - **๐Ÿค– AI agent context**: Give AI agents structured professional background on a person before a meeting or call *** ### โš ๏ธ Disclaimer This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedInยฎ is a registered trademark of LinkedIn Corporation. All trademarks are property of their respective owners. *** #### Dende Labs We build high-performance LinkedIn data tools for sales teams, recruiters, and growth professionals. Our actors are designed to be **fast**, **affordable**, and **developer-friendly**, with clean structured JSON output and pay-only-for-results pricing. - Built for scale: batch processing up to 5,000 profiles per run - No LinkedIn account required - Pay only for profiles that return data - Clean, structured JSON output, easy to join back to your data Questions or custom requests? Reach out at contact@dendelabs.com # Actor input Schema ## `profileUrls` (type: `array`): List of LinkedIn profile URLs to enrich. Each must match the format https://www.linkedin.com/in//. ## Actor input object example ```json { "profileUrls": [ "https://www.linkedin.com/in/satyanadella/" ] } ``` # Actor output Schema ## `profiles` (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 = { "profileUrls": [ "https://www.linkedin.com/in/satyanadella/" ] }; // Run the Actor and wait for it to finish const run = await client.actor("atomus/linkedin-profile-enricher").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "profileUrls": ["https://www.linkedin.com/in/satyanadella/"] } # Run the Actor and wait for it to finish run = client.actor("atomus/linkedin-profile-enricher").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "profileUrls": [ "https://www.linkedin.com/in/satyanadella/" ] }' | apify call atomus/linkedin-profile-enricher --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=atomus/linkedin-profile-enricher", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Profile Enricher PRO โœ… No Cookies", "description": "Enrich LinkedIn profiles with name, title, headline, summary, company, location, skills, education, and work history. Submit up to 5,000 URLs per run, each returns one structured record. Pay only for profiles found, not-found and errors are free. No LinkedIn account or cookies needed.", "version": "1.0", "x-build-id": "gHtlTrlbe74lILDhF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/atomus~linkedin-profile-enricher/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-atomus-linkedin-profile-enricher", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/atomus~linkedin-profile-enricher/runs": { "post": { "operationId": "runs-sync-atomus-linkedin-profile-enricher", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/atomus~linkedin-profile-enricher/run-sync": { "post": { "operationId": "run-sync-atomus-linkedin-profile-enricher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "profileUrls" ], "properties": { "profileUrls": { "title": "LinkedIn Profile URLs", "minItems": 1, "maxItems": 5000, "type": "array", "description": "List of LinkedIn profile URLs to enrich. Each must match the format https://www.linkedin.com/in//.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```