# Skool Email Scraper (`solid-scraper/skool-email-scraper`) Actor

📧 Skool Email Scraper extracts verified email addresses from Skool communities fast. Perfect for lead generation, outreach, and marketing teams seeking targeted contacts—save time, boost conversions, and streamline campaigns. 🚀

- **URL**: https://apify.com/solid-scraper/skool-email-scraper.md
- **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community)
- **Categories:** Lead generation, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

### Skool Email Scraper 🔍

**Skool Email Scraper** helps you extract email addresses from Skool profiles by using your chosen keywords and email-domain filters. If you’ve been searching for a **Skool email scraper** to build a **Skool lead generation scraper** pipeline (without manual copy-pasting), this actor automates the workflow: it finds emails mentioned in Skool bios/posts related to your keywords, then outputs structured results you can analyze or export at scale—saving you hours of manual work.

Whether you're a marketer, growth strategist, recruiter, or data enthusiast, this **Skool scraper email** tool is designed to support **extract emails from Skool** searches and turn them into a clean email list for outreach and research.  

---

### Why choose Skool Email Scraper?

| Feature | Benefit |
|---|---|
| ✅ **Keyword-driven email discovery** | Uses your provided keywords to focus results on the most relevant Skool community leads |
| ✅ **Custom email domain filtering** | Collects only the domains you specify (for example `@gmail.com`) to improve lead targeting |
| ✅ **Reliability with engine options** | Choose between engines to balance speed and reliability for different runs |
| ✅ **Structured output dataset** | Returns consistent fields like `email`, `keyword`, and source `url` so your workflow is predictable |
| ✅ **Built-in proxy support** | Improves stability for scraping at scale by using configurable proxy settings |
| ✅ **Scale-friendly controls** | Uses `maxEmails` to cap collection and keep runs controlled even when searches are large |

---

### Key features

- 🔎 **Skool email harvesting from public profiles:** Extracts emails from Skool bios and posts related to your keywords.
- 🧠 **Keyword-focused extraction:** Uses your keyword list to drive which results are processed, making this a practical **Skool contact scraper** for lead discovery.
- 🏷️ **Email-domain targeting:** Lets you limit output to specific domains with `customDomains`—great for **Skool DM email finder** style outreach lists.
- 🛡️ **Proxy + retry resilience:** Includes retries and fallbacks for resilience when scraping is blocked or returns empty results.
- 💾 **Real-time dataset saving:** Each discovered email is pushed to the dataset immediately so you don’t lose progress.
- 📊 **Deduplication of emails:** Avoids duplicate emails during the run using a `seen_emails` set.
- ⚙️ **Operational controls for large searches:** Uses `maxEmails` and run-time stop conditions to keep long runs under control.

---

### Input

Provide input via an `input.json` file. Example structure:

```json
{
  "keywords": ["founder", "marketing"],
  "location": "",
  "platform": "Skool",
  "customDomains": ["@gmail.com"],
  "maxEmails": 20,
  "engine": "legacy",
  "proxyConfiguration": {}
}
````

#### Input Fields

| Field | Required | Description |
|---|---:|---|
| `keywords` | ✅ | A list of keywords to search for. The actor uses these keywords to guide email discovery from Skool bios/posts. |
| `location` | ❌ | Location to filter search results. Leave it empty if you don’t need geographic targeting. |
| `platform` | ❌ | Select platform. The only available option in the input schema is `Skool` (default is `Skool`). |
| `customDomains` | ❌ | A list of custom email domains to include in results (for example `@gmail.com`). Using this helps you target the right inbox types for outreach. |
| `maxEmails` | ❌ | Maximum number of emails to collect. The scraper stops once this limit is reached, helping you control runtime and cost. Range is 1–10000 (default: 20). |
| `engine` | ❌ | Choose scraping engine: `cost-effective` or `legacy`. This is intended to balance speed vs reliability for your runs (default: `legacy`). |
| `proxyConfiguration` | ❌ | Proxy configuration for this Actor. You can set it up via Apify’s proxy editor UI to improve reliability during scraping. |

***

### Output

After execution, the actor pushes each discovered contact row into a dataset in JSON format. Each row includes the email plus the context needed for verification and outreach.

Example output row (one record):

```json
{
  "network": "Skool.com",
  "keyword": "founder",
  "title": "No data",
  "description": "No data",
  "url": "https://example.com/some-skool-page",
  "email": "example@gmail.com",
  "proxyGroups": ["GOOGLE_SERP"]
}
```

#### Output Fields

| Field | Type | Description |
|---|---|---|
| `network` | string | Source network label for the actor output (set to `Skool.com`). |
| `keyword` | string | The keyword currently driving the discovery for this record. |
| `title` | string | Title text associated with the source item (as captured from the parsed result). |
| `description` | string | Description text associated with the source item (may be `No data`). |
| `url` | string | URL of the source item where the email was found. |
| `email` | string | The extracted email address. |
| `proxyGroups` | array | The proxy group(s) used for this record, as an array (`user_proxy_group` or default list). |

You can export the resulting dataset as JSON or CSV from the Apify Console once the run completes.

***

### How to use Skool Email Scraper (via Apify Console)

1. **Open Apify Console**\
   Log in at [console.apify.com](https://console.apify.com) and go to the **Actors** tab.

2. **Find the actor**\
   Search for **Skool Email Scraper** and open the actor page.

3. **Open the INPUT panel**\
   Click the **INPUT** section in the right-side panel. Apify will show a form based on the input schema.

4. **Enter your keywords**\
   In **Keywords**, add the list you want to use (for example `founder`, `marketing`). `keywords` is required.

5. **Optionally refine targeting**\
   Set `customDomains` to include only specific inbox types (like `@gmail.com`). If needed, fill `location` for location filtering. Adjust `maxEmails` to control how many emails you want to collect in this run.

6. **Choose an engine & (optional) proxy settings**\
   Select `engine` (`cost-effective` or `legacy`). If you want higher reliability, configure `proxyConfiguration` using Apify’s proxy editor.

7. **Run the actor**\
   Click **Run**. During execution, the actor saves results to the dataset as it finds emails and stops once `maxEmails` is reached (or its internal stopping conditions trigger for empty/no-new-email runs).

8. **Review and export results**\
   After completion, open the **OUTPUT** dataset to preview records and export to JSON or CSV.

No coding required—you’ll be able to generate a **Skool member email list** workflow in minutes. ✅

***

### Advanced features & SEO optimization

- ⚙️ **Engine choice for speed vs reliability:** The **Skool email scraper** supports both `cost-effective` and `legacy` modes so you can tune runs for your needs (e.g., faster experimentation vs more conservative behavior).
- 🧾 **Stops safely using `maxEmails`:** Great for **bulk email extractor from Skool** use cases where you want predictable run sizes and controlled scraping time.
- 🧠 **Email-domain targeting with `customDomains`:** Improves outreach relevance by filtering to the inbox types you actually want.
- 💾 **Progress persistence:** The actor maintains progress internally and saves after pushing data to reduce the risk of losing work mid-run.
- 🔄 **Resilient handling for empty/blocked results:** Includes retries and stopping rules to avoid wasting time when a run yields no new emails.

***

### Best use cases

- 📈 **Growth teams building Skool outreach lists:** Generate a **Skool outreach email list** quickly by extracting emails tied to relevant keywords.
- 🎯 **B2B lead generation:** Use as a **Skool lead generation scraper** to identify community operators and potential partners for outreach.
- 🧪 **Market research & competitive analysis:** Build a dataset to analyze who is active in a niche and what email domains are used most.
- 🎓 **Recruiting sourcing:** Quickly compile contact information by searching for roles/themes like “founder” or “marketing” and exporting results to your ATS pipeline.
- 🗂️ **Data enrichment pipelines:** Feed extracted emails into CRM or marketing automation workflows using the consistent output fields (`email`, `url`, `keyword`).
- 👥 **Community partnerships:** Find **Skool contact scraper** candidates by focusing on niche keywords and filtering domains to your preferred outreach format.
- 💻 **Analyst workflows:** Combine the dataset with other sources by using the structured fields (`description`, `title`, `url`) for validation and auditing.

***

### Technical specifications

- **Supported Input Formats**
  - ✅ `keywords` (array of strings) as required input
  - ✅ `customDomains` (array of strings) for domain filtering
  - ✅ `maxEmails` (integer, 1–10000)
  - ✅ `engine` (`cost-effective` or `legacy`)
  - ✅ `proxyConfiguration` (proxy object)
  - ❌ No other platform values beyond `Skool` in the input schema

- **Proxy Support**
  - ✅ Configurable via `proxyConfiguration`
  - ✅ Actor supports proxy-based scraping for improved stability

- **Retry Mechanism**
  - ✅ Includes retries and fallbacks for resilience when requests fail or results are empty

- **Dataset Structure**
  - ✅ Each discovered item is pushed as a JSON row with:
    - `network`, `keyword`, `title`, `description`, `url`, `email`, `proxyGroups`

- **Rate Limits & Performance**
  - ⚠️ Large searches or high `maxEmails` may take longer (the input guidance notes that you may need to increase timeout in Run Options for large runs).

- **Limitations**
  - ❌ Only emails found in publicly available Skool bios/posts related to your keywords and matching your `customDomains` will be returned.
  - ❌ Setting a higher `maxEmails` does not guarantee that number will always be reached.

***

### FAQ

#### Does Skool Email Scraper require any login to run?

✅ No login credentials are part of the actor input schema. The actor is designed to scrape emails from publicly available sources and then push results into your dataset.

#### What exactly does Skool Email Scraper extract?

✅ It extracts email addresses that appear in Skool bios and posts related to your provided keywords, and it includes only emails matching the domains you specify via `customDomains`.

#### How do I make the results more targeted?

✅ Use specific `keywords` and set `customDomains` to the email domains you care about (for example `@gmail.com`). If results seem low, try broader keywords and add more related terms or more domains.

#### Why might I get fewer emails than expected?

❌ Results can be lower when searches are large, when emails don’t match your domain filters, or when scraping encounters empty/block outcomes. In those cases, rerun with broader keywords and more domains.

#### Can I control how many emails are collected?

✅ Yes. Use `maxEmails` to cap the maximum number of collected emails. The actor will stop once this limit is reached (though it does not guarantee the full number will be found).

#### Does it support proxies?

✅ Yes. You can configure `proxyConfiguration` in the input. The actor is also intended to be more resilient during scraping by using proxy settings and engine options.

#### Is there an API-friendly way to run this?

💻 Yes. You can run it programmatically by providing the same `input.json` fields documented above (especially `keywords`, `customDomains`, `maxEmails`, `engine`, and `proxyConfiguration`).

#### Is it legal to scrape emails from Skool?

✅ The actor collects information only from **publicly accessible sources**. You’re responsible for complying with applicable laws and platform terms (including GDPR/CCPA where relevant) and using the data appropriately.

***

### Support & feature requests

Want to improve your Skool email scraper workflow? 💡 Share feedback or feature requests to help strengthen **Skool Email Scraper**.

- 💡 **Feature Requests:** Examples include adding CSV-focused output convenience, expanding export options, or improving filtering logic for **Skool member email list** workflows.
- 📧 **Contact:** For help or custom requests, email us at <dataforleads@gmail.com>.

Your feedback helps shape the roadmap for this **Skool scraper email** tool—so your results keep getting better. 🚀

***

### *Skool Email Scraper* — Final thoughts

*If you need an SEO-optimized automated Skool email harvesting workflow, **Skool Email Scraper** gives you structured results you can export fast.*\
*Run it with the right keywords and domain filters to turn Skool communities into actionable leads at scale.* 🎯

***

### Disclaimer

**This tool only accesses publicly accessible sources.** It does not access private profiles, authenticated data, or password-protected content.

You are responsible for complying with applicable laws and regulations (including GDPR/CCPA where relevant), as well as respecting platform terms of service and spam/email regulations. For data removal requests, contact <dataforleads@gmail.com>.

Please use **Skool Email Scraper** responsibly, ethically, and for legitimate purposes only.

# Actor input Schema

## `keywords` (type: `array`):

A list of keywords to search for.

## `location` (type: `string`):

Location to filter search results.

## `platform` (type: `string`):

Select platform.

## `customDomains` (type: `array`):

List of custom email domains

## `maxEmails` (type: `integer`):

Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.

## `engine` (type: `string`):

Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive.

## `proxyConfiguration` (type: `object`):

Configure proxies for this Actor.

## Actor input object example

```json
{
  "keywords": [
    "founder",
    "marketing"
  ],
  "location": "",
  "platform": "Skool",
  "customDomains": [
    "@gmail.com"
  ],
  "maxEmails": 20,
  "engine": "legacy"
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "founder",
        "marketing"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("solid-scraper/skool-email-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": [
        "founder",
        "marketing",
    ],
    "location": "",
    "customDomains": ["@gmail.com"],
}

# Run the Actor and wait for it to finish
run = client.actor("solid-scraper/skool-email-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 '{
  "keywords": [
    "founder",
    "marketing"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com"
  ]
}' |
apify call solid-scraper/skool-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=solid-scraper/skool-email-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Skool Email Scraper",
        "description": "📧 Skool Email Scraper extracts verified email addresses from Skool communities fast. Perfect for lead generation, outreach, and marketing teams seeking targeted contacts—save time, boost conversions, and streamline campaigns. 🚀",
        "version": "0.0",
        "x-build-id": "FrEi1q9JeS1MZ92ym"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/solid-scraper~skool-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-solid-scraper-skool-email-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/solid-scraper~skool-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-solid-scraper-skool-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/solid-scraper~skool-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-solid-scraper-skool-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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",
                "required": [
                    "keywords"
                ],
                "properties": {
                    "keywords": {
                        "title": "Keywords",
                        "type": "array",
                        "description": "A list of keywords to search for.",
                        "default": [
                            "founder",
                            "marketing"
                        ],
                        "items": {
                            "type": "string"
                        }
                    },
                    "location": {
                        "title": "Location",
                        "type": "string",
                        "description": "Location to filter search results.",
                        "default": ""
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Skool"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Skool"
                    },
                    "customDomains": {
                        "title": "Custom Email Domains",
                        "type": "array",
                        "description": "List of custom email domains",
                        "default": [
                            "@gmail.com"
                        ],
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxEmails": {
                        "title": "Max Emails",
                        "minimum": 1,
                        "maximum": 10000,
                        "type": "integer",
                        "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.",
                        "default": 20
                    },
                    "engine": {
                        "title": "Engine",
                        "enum": [
                            "cost-effective",
                            "legacy"
                        ],
                        "type": "string",
                        "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.",
                        "default": "legacy"
                    },
                    "proxyConfiguration": {
                        "title": "Proxy Configuration",
                        "type": "object",
                        "description": "Configure proxies for this Actor."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```