# AI Search Visibility Gap Scorer (`rotvuvo/ai-search-visibility-gap-scorer`) Actor

Turn imported AI-search, SERP, and AI Overview visibility rows into deterministic visibility gap scores and next actions.

- **URL**: https://apify.com/rotvuvo/ai-search-visibility-gap-scorer.md
- **Developed by:** [Wit Nomad](https://apify.com/rotvuvo) (community)
- **Categories:** AI, SEO tools, Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

## AI Search Visibility Gap Scorer

Ingest-first Apify Actor that turns imported AI-search/SERP/AIO visibility rows into deterministic visibility-gap scores and next actions.

It is for SEO/GEO agencies, content marketers, and SaaS growth teams that already collect rows from existing Apify SERP, Google AI Overview, AI brand monitor, spreadsheet, or manual audit workflows and need a client-ready prioritization layer.

### What it does

- Normalizes imported AI-search/SERP/AIO visibility rows.
- Scores whether your brand is missing, mentioned without citations, covered by owned sources, or losing visibility to competitors.
- Produces query-level `visibilityGapScore`, `shareOfVoice`, `gapType`, evidence snippets, citation opportunities, and next actions.
- Runs without live AI/search calls, API keys, scraping, or proxies.

### Input

Use `items` mode with rows from upstream tools. Common aliases are supported:

- `query`, `prompt`, `keyword`, `searchTerm`, `topic`
- `engine`, `platform`, `provider`, `model`, `searchEngine`
- `locale`, `country`, `language`, `market`
- `answer`, `aiAnswer`, `overview`, `summary`, `snippet`
- `citations`, `sources`, `references`, `links`, `organicResults`
- `brandMentioned`, `mentions`, `mentionedBrands`, `entities`
- `competitorMentions`, `competitors`, `competingBrands`

Optional `brandProfile` fields include `brandName`, `domains`, `competitors`, `ownedSources`, and `preferredCitations`.

### Output

Each dataset item represents a deduped query/engine/locale row with:

- visibility and share-of-voice scores
- brand and competitor evidence counts
- gap classification
- citation/source opportunities
- content actions and report-ready notes
- confidence, warnings, and missing evidence

### Important limitations

This Actor analyzes imported rows only. It does not call ChatGPT. It does not call Claude. It does not call Gemini. It does not call Perplexity. It does not call Google, Bing, or any live AI/search service. It does not scrape Google. It does not scrape Bing. It does not scrape ChatGPT, Perplexity, or any other engine. It does not use proxies. It does not provide real-time monitoring unless you schedule upstream data collection separately. It does not guarantee AI citations. It does not guarantee rankings, traffic, revenue, or SEO outcomes.

### Local verification

From the repository root, run the local quality gate for this Actor.

# Actor input Schema

## `mode` (type: `string`):

Input mode. This version supports pasted/imported AI-search, SERP, Google AI Overview, or manual visibility audit rows only.
## `items` (type: `array`):

Rows from existing Apify SERP, Google AI Overview, AI brand monitor, spreadsheet, or manual audit datasets. Common fields: query/prompt/keyword/searchTerm, engine/platform/provider/model, locale/country/language, answer/aiAnswer/overview/summary/snippet, citations/sources/references/organicResults, brandMentioned/mentionedBrands, competitorMentions/competingBrands.
## `brandProfile` (type: `object`):

Optional brand and competitor context used for deterministic matching. Domain ownership is used only for citation/source checks; brand/competitor names are not matched from URL text alone.
## `maxItems` (type: `integer`):

Maximum imported rows to process.
## `scrapedAt` (type: `string`):

Optional ISO timestamp for deterministic output metadata. This Actor does not scrape; when omitted or invalid, the runtime uses this fixed default reference timestamp.

## Actor input object example

```json
{
  "mode": "items",
  "items": [
    {
      "query": "best product analytics tools for b2b saas",
      "engine": "Perplexity manual export",
      "locale": "US",
      "answer": "RivalMetrics is frequently recommended for B2B SaaS product analytics. Northstar BI is also mentioned.",
      "citations": [
        {
          "title": "RivalMetrics customer story",
          "url": "https://rivalmetrics.com/customers/b2b-saas"
        },
        {
          "title": "Product analytics software rankings",
          "url": "https://g2.com/categories/product-analytics"
        }
      ]
    },
    {
      "prompt": "is acme analytics good for product teams",
      "platform": "ChatGPT manual audit",
      "market": "US",
      "aiAnswer": "Acme Analytics is a possible product analytics option, but buyers often compare it with RivalMetrics.",
      "sources": [
        {
          "title": "Third-party product analytics roundup",
          "url": "https://example-review-site.com/product-analytics"
        }
      ]
    },
    {
      "keyword": "acme analytics implementation guide",
      "provider": "Google AI Overview export",
      "country": "US",
      "overview": "Acme Analytics provides implementation guidance for product teams, including event tracking and activation reporting.",
      "organicResults": [
        {
          "title": "Acme Analytics implementation guide",
          "url": "https://docs.acmeanalytics.com/implementation"
        },
        {
          "title": "Acme Analytics product analytics blog",
          "url": "https://blog.acmeanalytics.com/product-analytics-guide"
        }
      ],
      "mentionedBrands": [
        "Acme Analytics"
      ]
    }
  ],
  "brandProfile": {
    "brandName": "Acme Analytics",
    "domains": [
      "acmeanalytics.com"
    ],
    "competitors": [
      "RivalMetrics",
      "Northstar BI"
    ],
    "targetMarkets": [
      "US SaaS"
    ],
    "targetKeywords": [
      "product analytics",
      "AI visibility"
    ],
    "priorityTopics": [
      "B2B SaaS analytics",
      "implementation guides"
    ],
    "ownedSources": [
      "docs.acmeanalytics.com",
      "blog.acmeanalytics.com"
    ],
    "preferredCitations": [
      "g2.com",
      "capterra.com",
      "docs.acmeanalytics.com"
    ],
    "avoidKeywords": [
      "guaranteed ranking"
    ]
  },
  "maxItems": 500,
  "scrapedAt": "2026-07-08T00:00:00.000Z"
}
````

# 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 = {
    "mode": "items",
    "items": [
        {
            "query": "best product analytics tools for b2b saas",
            "engine": "Perplexity manual export",
            "locale": "US",
            "answer": "RivalMetrics is frequently recommended for B2B SaaS product analytics. Northstar BI is also mentioned.",
            "citations": [
                {
                    "title": "RivalMetrics customer story",
                    "url": "https://rivalmetrics.com/customers/b2b-saas"
                },
                {
                    "title": "Product analytics software rankings",
                    "url": "https://g2.com/categories/product-analytics"
                }
            ]
        },
        {
            "prompt": "is acme analytics good for product teams",
            "platform": "ChatGPT manual audit",
            "market": "US",
            "aiAnswer": "Acme Analytics is a possible product analytics option, but buyers often compare it with RivalMetrics.",
            "sources": [
                {
                    "title": "Third-party product analytics roundup",
                    "url": "https://example-review-site.com/product-analytics"
                }
            ]
        },
        {
            "keyword": "acme analytics implementation guide",
            "provider": "Google AI Overview export",
            "country": "US",
            "overview": "Acme Analytics provides implementation guidance for product teams, including event tracking and activation reporting.",
            "organicResults": [
                {
                    "title": "Acme Analytics implementation guide",
                    "url": "https://docs.acmeanalytics.com/implementation"
                },
                {
                    "title": "Acme Analytics product analytics blog",
                    "url": "https://blog.acmeanalytics.com/product-analytics-guide"
                }
            ],
            "mentionedBrands": [
                "Acme Analytics"
            ]
        }
    ],
    "brandProfile": {
        "brandName": "Acme Analytics",
        "domains": [
            "acmeanalytics.com"
        ],
        "competitors": [
            "RivalMetrics",
            "Northstar BI"
        ],
        "targetMarkets": [
            "US SaaS"
        ],
        "targetKeywords": [
            "product analytics",
            "AI visibility"
        ],
        "priorityTopics": [
            "B2B SaaS analytics",
            "implementation guides"
        ],
        "ownedSources": [
            "docs.acmeanalytics.com",
            "blog.acmeanalytics.com"
        ],
        "preferredCitations": [
            "g2.com",
            "capterra.com",
            "docs.acmeanalytics.com"
        ],
        "avoidKeywords": [
            "guaranteed ranking"
        ]
    },
    "scrapedAt": "2026-07-08T00:00:00.000Z"
};

// Run the Actor and wait for it to finish
const run = await client.actor("rotvuvo/ai-search-visibility-gap-scorer").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 = {
    "mode": "items",
    "items": [
        {
            "query": "best product analytics tools for b2b saas",
            "engine": "Perplexity manual export",
            "locale": "US",
            "answer": "RivalMetrics is frequently recommended for B2B SaaS product analytics. Northstar BI is also mentioned.",
            "citations": [
                {
                    "title": "RivalMetrics customer story",
                    "url": "https://rivalmetrics.com/customers/b2b-saas",
                },
                {
                    "title": "Product analytics software rankings",
                    "url": "https://g2.com/categories/product-analytics",
                },
            ],
        },
        {
            "prompt": "is acme analytics good for product teams",
            "platform": "ChatGPT manual audit",
            "market": "US",
            "aiAnswer": "Acme Analytics is a possible product analytics option, but buyers often compare it with RivalMetrics.",
            "sources": [{
                    "title": "Third-party product analytics roundup",
                    "url": "https://example-review-site.com/product-analytics",
                }],
        },
        {
            "keyword": "acme analytics implementation guide",
            "provider": "Google AI Overview export",
            "country": "US",
            "overview": "Acme Analytics provides implementation guidance for product teams, including event tracking and activation reporting.",
            "organicResults": [
                {
                    "title": "Acme Analytics implementation guide",
                    "url": "https://docs.acmeanalytics.com/implementation",
                },
                {
                    "title": "Acme Analytics product analytics blog",
                    "url": "https://blog.acmeanalytics.com/product-analytics-guide",
                },
            ],
            "mentionedBrands": ["Acme Analytics"],
        },
    ],
    "brandProfile": {
        "brandName": "Acme Analytics",
        "domains": ["acmeanalytics.com"],
        "competitors": [
            "RivalMetrics",
            "Northstar BI",
        ],
        "targetMarkets": ["US SaaS"],
        "targetKeywords": [
            "product analytics",
            "AI visibility",
        ],
        "priorityTopics": [
            "B2B SaaS analytics",
            "implementation guides",
        ],
        "ownedSources": [
            "docs.acmeanalytics.com",
            "blog.acmeanalytics.com",
        ],
        "preferredCitations": [
            "g2.com",
            "capterra.com",
            "docs.acmeanalytics.com",
        ],
        "avoidKeywords": ["guaranteed ranking"],
    },
    "scrapedAt": "2026-07-08T00:00:00.000Z",
}

# Run the Actor and wait for it to finish
run = client.actor("rotvuvo/ai-search-visibility-gap-scorer").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 '{
  "mode": "items",
  "items": [
    {
      "query": "best product analytics tools for b2b saas",
      "engine": "Perplexity manual export",
      "locale": "US",
      "answer": "RivalMetrics is frequently recommended for B2B SaaS product analytics. Northstar BI is also mentioned.",
      "citations": [
        {
          "title": "RivalMetrics customer story",
          "url": "https://rivalmetrics.com/customers/b2b-saas"
        },
        {
          "title": "Product analytics software rankings",
          "url": "https://g2.com/categories/product-analytics"
        }
      ]
    },
    {
      "prompt": "is acme analytics good for product teams",
      "platform": "ChatGPT manual audit",
      "market": "US",
      "aiAnswer": "Acme Analytics is a possible product analytics option, but buyers often compare it with RivalMetrics.",
      "sources": [
        {
          "title": "Third-party product analytics roundup",
          "url": "https://example-review-site.com/product-analytics"
        }
      ]
    },
    {
      "keyword": "acme analytics implementation guide",
      "provider": "Google AI Overview export",
      "country": "US",
      "overview": "Acme Analytics provides implementation guidance for product teams, including event tracking and activation reporting.",
      "organicResults": [
        {
          "title": "Acme Analytics implementation guide",
          "url": "https://docs.acmeanalytics.com/implementation"
        },
        {
          "title": "Acme Analytics product analytics blog",
          "url": "https://blog.acmeanalytics.com/product-analytics-guide"
        }
      ],
      "mentionedBrands": [
        "Acme Analytics"
      ]
    }
  ],
  "brandProfile": {
    "brandName": "Acme Analytics",
    "domains": [
      "acmeanalytics.com"
    ],
    "competitors": [
      "RivalMetrics",
      "Northstar BI"
    ],
    "targetMarkets": [
      "US SaaS"
    ],
    "targetKeywords": [
      "product analytics",
      "AI visibility"
    ],
    "priorityTopics": [
      "B2B SaaS analytics",
      "implementation guides"
    ],
    "ownedSources": [
      "docs.acmeanalytics.com",
      "blog.acmeanalytics.com"
    ],
    "preferredCitations": [
      "g2.com",
      "capterra.com",
      "docs.acmeanalytics.com"
    ],
    "avoidKeywords": [
      "guaranteed ranking"
    ]
  },
  "scrapedAt": "2026-07-08T00:00:00.000Z"
}' |
apify call rotvuvo/ai-search-visibility-gap-scorer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=rotvuvo/ai-search-visibility-gap-scorer",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "AI Search Visibility Gap Scorer",
        "description": "Turn imported AI-search, SERP, and AI Overview visibility rows into deterministic visibility gap scores and next actions.",
        "version": "0.1",
        "x-build-id": "kVnOXnWABhbH5o2d3"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/rotvuvo~ai-search-visibility-gap-scorer/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-rotvuvo-ai-search-visibility-gap-scorer",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/rotvuvo~ai-search-visibility-gap-scorer/runs": {
            "post": {
                "operationId": "runs-sync-rotvuvo-ai-search-visibility-gap-scorer",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/rotvuvo~ai-search-visibility-gap-scorer/run-sync": {
            "post": {
                "operationId": "run-sync-rotvuvo-ai-search-visibility-gap-scorer",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "items"
                ],
                "properties": {
                    "mode": {
                        "title": "Mode",
                        "enum": [
                            "items"
                        ],
                        "type": "string",
                        "description": "Input mode. This version supports pasted/imported AI-search, SERP, Google AI Overview, or manual visibility audit rows only.",
                        "default": "items"
                    },
                    "items": {
                        "title": "Imported visibility rows",
                        "minItems": 1,
                        "type": "array",
                        "description": "Rows from existing Apify SERP, Google AI Overview, AI brand monitor, spreadsheet, or manual audit datasets. Common fields: query/prompt/keyword/searchTerm, engine/platform/provider/model, locale/country/language, answer/aiAnswer/overview/summary/snippet, citations/sources/references/organicResults, brandMentioned/mentionedBrands, competitorMentions/competingBrands.",
                        "items": {
                            "type": "object"
                        }
                    },
                    "brandProfile": {
                        "title": "Brand profile",
                        "type": "object",
                        "description": "Optional brand and competitor context used for deterministic matching. Domain ownership is used only for citation/source checks; brand/competitor names are not matched from URL text alone."
                    },
                    "maxItems": {
                        "title": "Maximum rows",
                        "minimum": 1,
                        "maximum": 5000,
                        "type": "integer",
                        "description": "Maximum imported rows to process.",
                        "default": 500
                    },
                    "scrapedAt": {
                        "title": "Reference timestamp",
                        "type": "string",
                        "description": "Optional ISO timestamp for deterministic output metadata. This Actor does not scrape; when omitted or invalid, the runtime uses this fixed default reference timestamp.",
                        "default": "2026-07-08T00:00:00.000Z"
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```