# Steam Review & Comment Intelligence Scraper (`lokki/steam-comments-intelligence-scraper`) Actor

Scrape public Steam game reviews/comments and turn player feedback into product intelligence: sentiment, complaints, bug reports, feature requests, pricing objections, praise, toxicity flags, opportunity scores, and recommended actions.

- **URL**: https://apify.com/lokki/steam-comments-intelligence-scraper.md
- **Developed by:** [Ian Dikhtiar](https://apify.com/lokki) (community)
- **Categories:** Automation, Lead generation, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 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

## Steam Review & Comment Intelligence Scraper

Steam reviews are where players tell you exactly why they buy, refund, rage, recommend, complain, and keep playing.

This actor scrapes public Steam game reviews/comments and turns them into **voice-of-customer intelligence**: sentiment, complaints, praise, bugs, feature requests, pricing objections, opportunity scores, summaries, and recommended actions.

Use it with the Steam Market Intelligence actor: first find interesting games, then mine their reviews to understand the market’s actual language.

### What this is really for

Use it to answer questions like:

- Why do players love this competitor?
- What are players complaining about repeatedly?
- Are negative reviews caused by bugs, pricing, missing content, balance, UX, or community issues?
- Which comments contain feature requests?
- Which reviews are useful enough for roadmap, ad copy, landing pages, or competitor teardown?
- What exact words do players use to describe value, frustration, fun, grind, bugs, and pricing?

### Best use cases

- **Competitor teardown** — pull negative reviews from rival games and find recurring weaknesses.
- **Game positioning** — mine positive reviews for the exact language players use when they love a game.
- **Feature research** — detect “wish it had…” and “please add…” patterns.
- **Bug/performance research** — cluster crash, lag, stutter, and unplayable complaints.
- **Pricing research** — surface refund, overpriced, DLC, microtransaction, and paywall objections.
- **AI/RAG datasets** — every row can include clean markdown ready for LLM workflows.

### What you get

#### Core Steam review fields

- App ID
- Game title
- Recommendation/review ID
- Review URL
- Review text
- Recommended / not recommended
- Language
- Created and updated timestamps
- Author Steam ID
- Playtime forever
- Playtime at review
- Playtime last two weeks
- Helpful votes
- Funny votes
- Weighted vote score
- Comment count
- Steam purchase flag
- Received-for-free flag
- Early-access review flag
- Steam Deck flag

#### Comment intelligence fields

- `sentimentScore`
- `sentimentLabel`
- `painScore`
- `praiseScore`
- `usefulnessScore`
- `opportunityScore`
- `matchedTopics`
- `complaintSignals`
- `praiseSignals`
- `bugSignal`
- `featureRequestSignal`
- `pricingSignal`
- `toxicitySignal`
- `commentSummary`
- `recommendedAction`
- `ragMarkdown`

### The intelligence layer

#### `sentimentScore` and `sentimentLabel`

Combines the Steam recommendation flag with positive and negative language. Labels each review as `positive`, `mixed`, or `negative`.

#### `painScore`

Finds reviews that reveal useful pain: bugs, crashes, lag, pricing objections, lack of content, bad balance, bad UX, cheating, toxic community, refund language, and “not worth it” complaints.

High pain is useful for competitor displacement research.

#### `praiseScore`

Finds reviews that explain why players love a game: fun core loop, strong value, polish, multiplayer/friends, atmosphere, content depth, replayability, and smooth performance.

High praise is useful for positioning and copywriting.

#### `usefulnessScore`

Ranks comments by research value using length, topic coverage, helpful votes, and player playtime.

A short meme review is less useful than a detailed review from someone with 100+ hours.

#### `opportunityScore`

The headline score. Prioritizes reviews that contain useful pain, high detail, topic signals, helpful votes, and feature-request language.

Sort by this when you want the comments most worth reading first.

#### Topic and signal detection

The actor detects topics like:

- performance
- bugs
- multiplayer
- balance
- pricing
- content
- controls / UX
- graphics / audio
- modding

It also labels complaint and praise patterns so you can quickly cluster feedback.

### Example input

```json
{
  "appIds": ["730", "230410"],
  "maxCommentsPerGame": 100,
  "filter": "recent",
  "reviewType": "all",
  "purchaseType": "all",
  "language": "english",
  "includeIntelligence": true
}
````

### Recommended presets

#### Mine competitor weaknesses

```json
{
  "appIds": ["730"],
  "maxCommentsPerGame": 300,
  "filter": "recent",
  "reviewType": "negative",
  "language": "english",
  "includeIntelligence": true
}
```

#### Mine player praise for positioning

```json
{
  "appIds": ["230410"],
  "maxCommentsPerGame": 300,
  "filter": "recent",
  "reviewType": "positive",
  "language": "english",
  "includeIntelligence": true
}
```

#### Build a feature-request dataset

```json
{
  "steamUrls": ["https://store.steampowered.com/app/3124540/Far_Far_West/"],
  "maxCommentsPerGame": 500,
  "filter": "all",
  "reviewType": "all",
  "language": "english",
  "includeIntelligence": true
}
```

### Example output

```json
{
  "appId": 730,
  "gameTitle": "Counter-Strike 2",
  "recommendationId": "123456789",
  "isRecommended": false,
  "reviewText": "The game is fun but the cheating and stutters make it hard to recommend.",
  "playtimeForeverHours": 248.4,
  "votesUp": 12,
  "sentimentLabel": "negative",
  "painScore": 82,
  "praiseScore": 18,
  "usefulnessScore": 75,
  "opportunityScore": 79,
  "matchedTopics": ["performance", "bugs", "multiplayer"],
  "complaintSignals": ["buggy or unstable", "community or cheating problem"],
  "bugSignal": true,
  "featureRequestSignal": false,
  "pricingSignal": false,
  "commentSummary": "Player did not recommend the game; sentiment is negative; pain 82/100; praise 18/100. Topics: performance, bugs, multiplayer. Complaints: buggy or unstable, community or cheating problem.",
  "recommendedAction": "Prioritize as bug/performance evidence; cluster with similar reviews before roadmap decisions."
}
```

### Input guide

#### Steam app IDs

Paste one or more app IDs. The app ID is the number in a Steam store URL.

Example:

`https://store.steampowered.com/app/730/CounterStrike_2/`

App ID: `730`

#### Steam URLs

If you do not want to extract IDs manually, paste Steam app URLs. The actor extracts IDs automatically.

#### Comments per game

- `25` — fast test
- `100` — useful snapshot
- `300-500` — strong research set
- `1000+` — deeper VOC mining

#### Review feed

- **Recent reviews** — best for current sentiment.
- **Updated reviews** — useful for changed player opinions.
- **All reviews** — broader historical research.

#### Review sentiment

- **All reviews** — balanced research.
- **Negative only** — best for pain, bugs, pricing objections, and competitor weaknesses.
- **Positive only** — best for praise, positioning, and copywriting.

#### Language

English is recommended for best intelligence classification.

Use `all` if you want every available language, but keyword-based intelligence will be weaker outside English.

### Notes and limitations

- Uses public Steam review endpoints.
- Does not log in.
- Does not scrape private user data.
- Does not bypass age gates, login walls, or account pages.
- Steam may not expose reviews for every app, unreleased title, demo, DLC-like item, or restricted page.
- Built-in intelligence is deterministic keyword scoring, not an LLM call, so it is fast and explainable.

### Output destinations

Results are saved to the default Apify dataset.

A `SUMMARY` record is saved to the default key-value store with run settings, counts, and generated fields.

# Actor input Schema

## `appIds` (type: `array`):

One or more Steam app IDs to scrape reviews/comments from.

## `steamUrls` (type: `array`):

Optional. Paste Steam app URLs like https://store.steampowered.com/app/730/CounterStrike\_2/. App IDs will be extracted automatically.

## `maxCommentsPerGame` (type: `integer`):

Maximum number of public Steam reviews/comments to save per game.

## `filter` (type: `string`):

Recent finds current player sentiment. Updated catches changed reviews. All is broader historical coverage.

## `reviewType` (type: `string`):

Use negative to mine complaints and competitor weaknesses. Use positive to understand what players love.

## `purchaseType` (type: `string`):

Usually leave as All. Steam purchase can reduce key/free-copy noise.

## `language` (type: `string`):

Steam review language. Examples: english, all, german, spanish, french, schinese.

## `dayRange` (type: `integer`):

Optional. Limit reviews to approximately this many recent days. Leave empty or 0 for no day filter.

## `includeIntelligence` (type: `boolean`):

Recommended on. Adds sentiment, pain/praise categories, bug/feature/pricing signals, toxicity flags, usefulness score, opportunity score, summary, and recommended action.

## `includeRawReview` (type: `boolean`):

Turn on only for debugging or custom parsing. It makes rows larger.

## `requestDelayMs` (type: `integer`):

Polite delay in milliseconds between Steam review API pages.

## Actor input object example

```json
{
  "appIds": [
    "730",
    "230410"
  ],
  "steamUrls": [
    "https://store.steampowered.com/app/730/CounterStrike_2/"
  ],
  "maxCommentsPerGame": 100,
  "filter": "recent",
  "reviewType": "all",
  "purchaseType": "all",
  "language": "english",
  "includeIntelligence": true,
  "includeRawReview": false,
  "requestDelayMs": 250
}
```

# Actor output Schema

## `results` (type: `string`):

Default dataset items produced by the actor.

## `summary` (type: `string`):

Summary JSON stored in the default key-value store.

# 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 = {
    "appIds": [
        "730",
        "230410"
    ],
    "steamUrls": [
        "https://store.steampowered.com/app/730/CounterStrike_2/"
    ],
    "language": "english"
};

// Run the Actor and wait for it to finish
const run = await client.actor("lokki/steam-comments-intelligence-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 = {
    "appIds": [
        "730",
        "230410",
    ],
    "steamUrls": ["https://store.steampowered.com/app/730/CounterStrike_2/"],
    "language": "english",
}

# Run the Actor and wait for it to finish
run = client.actor("lokki/steam-comments-intelligence-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 '{
  "appIds": [
    "730",
    "230410"
  ],
  "steamUrls": [
    "https://store.steampowered.com/app/730/CounterStrike_2/"
  ],
  "language": "english"
}' |
apify call lokki/steam-comments-intelligence-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Steam Review & Comment Intelligence Scraper",
        "description": "Scrape public Steam game reviews/comments and turn player feedback into product intelligence: sentiment, complaints, bug reports, feature requests, pricing objections, praise, toxicity flags, opportunity scores, and recommended actions.",
        "version": "1.0",
        "x-build-id": "t3qhenXGb0o2OoAOh"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/lokki~steam-comments-intelligence-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-lokki-steam-comments-intelligence-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/lokki~steam-comments-intelligence-scraper/runs": {
            "post": {
                "operationId": "runs-sync-lokki-steam-comments-intelligence-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/lokki~steam-comments-intelligence-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-lokki-steam-comments-intelligence-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "maxCommentsPerGame"
                ],
                "properties": {
                    "appIds": {
                        "title": "Steam app IDs",
                        "type": "array",
                        "description": "One or more Steam app IDs to scrape reviews/comments from.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "steamUrls": {
                        "title": "Or paste Steam game URLs",
                        "type": "array",
                        "description": "Optional. Paste Steam app URLs like https://store.steampowered.com/app/730/CounterStrike_2/. App IDs will be extracted automatically.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxCommentsPerGame": {
                        "title": "Comments per game",
                        "minimum": 1,
                        "maximum": 5000,
                        "type": "integer",
                        "description": "Maximum number of public Steam reviews/comments to save per game.",
                        "default": 100
                    },
                    "filter": {
                        "title": "Review feed",
                        "enum": [
                            "recent",
                            "updated",
                            "all"
                        ],
                        "type": "string",
                        "description": "Recent finds current player sentiment. Updated catches changed reviews. All is broader historical coverage.",
                        "default": "recent"
                    },
                    "reviewType": {
                        "title": "Review sentiment to collect",
                        "enum": [
                            "all",
                            "positive",
                            "negative"
                        ],
                        "type": "string",
                        "description": "Use negative to mine complaints and competitor weaknesses. Use positive to understand what players love.",
                        "default": "all"
                    },
                    "purchaseType": {
                        "title": "Purchase source",
                        "enum": [
                            "all",
                            "steam",
                            "non_steam_purchase"
                        ],
                        "type": "string",
                        "description": "Usually leave as All. Steam purchase can reduce key/free-copy noise.",
                        "default": "all"
                    },
                    "language": {
                        "title": "Review language",
                        "type": "string",
                        "description": "Steam review language. Examples: english, all, german, spanish, french, schinese.",
                        "default": "english"
                    },
                    "dayRange": {
                        "title": "Only recent days",
                        "minimum": 0,
                        "maximum": 3650,
                        "type": "integer",
                        "description": "Optional. Limit reviews to approximately this many recent days. Leave empty or 0 for no day filter."
                    },
                    "includeIntelligence": {
                        "title": "Add comment intelligence",
                        "type": "boolean",
                        "description": "Recommended on. Adds sentiment, pain/praise categories, bug/feature/pricing signals, toxicity flags, usefulness score, opportunity score, summary, and recommended action.",
                        "default": true
                    },
                    "includeRawReview": {
                        "title": "Include raw Steam review object",
                        "type": "boolean",
                        "description": "Turn on only for debugging or custom parsing. It makes rows larger.",
                        "default": false
                    },
                    "requestDelayMs": {
                        "title": "Delay between review pages",
                        "minimum": 0,
                        "maximum": 5000,
                        "type": "integer",
                        "description": "Polite delay in milliseconds between Steam review API pages.",
                        "default": 250
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```