# WeChat Chat Export Analyzer — Group Insights & Action Items (`scrupulous_buckler/wechat-chat-export-analyzer-group-insights-action-items`) Actor

Analyze user-provided WeChat chat and group export records for questions, needs, concerns, decisions, action items, supplied brand and competitor mentions, participation patterns, and evidence windows. No WeChat login or chat extraction.

- **URL**: https://apify.com/scrupulous\_buckler/wechat-chat-export-analyzer-group-insights-action-items.md
- **Developed by:** [Peng Lyu](https://apify.com/scrupulous_buckler) (community)
- **Categories:** Social media, Business, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.99 / up to 2,000 messages and full group insights report

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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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/docs.md):

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

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

## WeChat Chat Export Analyzer — Group Insights & Action Items

Analyze **user-provided** WeChat chat and group export records for recurring
questions, needs, concerns, decisions, action items, supplied brand and
competitor mentions, participation patterns, time patterns, and auditable
conversation windows.

**This Actor analyzes records the customer supplies. It does not log in to
WeChat, scrape private chats, extract local databases, bypass encryption,
control an account, or obtain chat records from a phone or computer.**

**Unofficial tool. This Actor is not affiliated with, sponsored by, or endorsed
by Tencent, WeChat, or Weixin.**

### What the customer buys

One successful report costs **$4.99** and analyzes up to **2,000 normalized
messages**.

The delivery contains:

- one privacy-aware row per normalized message
- transparent sentiment and intent labels
- exact supplied keyword, brand, product and competitor counts
- questions, needs and concerns with evidence
- decision and action-item signals with evidence
- nearby conversation windows around selected decisions and tasks
- participant, chat, daily and hourly activity patterns
- data-quality and coverage warnings

No usable messages means no report event is created.

### This is not a chat extraction tool

The title deliberately says **Chat Export Analyzer**. Customers must first
export, transform or otherwise lawfully obtain records they are authorized to
analyze. Outside demo mode they must confirm `hasRightToAnalyze`.

Do not use this Actor to process private or confidential conversations without
the required ownership, consent, authority and lawful basis.

### Input modes

#### 1. Static example preview

The default demo analyzes 12 clearly labeled synthetic messages across a
project group and a customer-feedback group. It demonstrates the complete
delivery without triggering the $4.99 custom report event. Apify may still show
the small Actor-start or platform usage charge.

#### 2. Existing Apify Datasets

```json
{
  "mode": "datasetMessages",
  "sourceDatasetIds": ["YOUR_DATASET_ID"],
  "hasRightToAnalyze": true,
  "researchTopic": "Product launch customer feedback",
  "messageKeywords": ["价格", "退款", "发货", "副作用"],
  "knownEntities": ["产品甲"],
  "competitorNames": ["产品乙"],
  "privacyMode": "anonymizeParticipants",
  "redactContactDetails": true,
  "maxMessages": 2000
}
````

#### 3. Uploaded JSON records

```json
{
  "mode": "uploadedMessages",
  "hasRightToAnalyze": true,
  "researchTopic": "Campaign operations group",
  "uploadedMessages": [
    {
      "message_id": "m1",
      "chat_name": "Campaign group",
      "sender": "Member A",
      "timestamp": "2026-07-20 09:10:00",
      "content": "客户一直问价格和退款条件，怎么回答？"
    },
    {
      "message_id": "m2",
      "chat_name": "Campaign group",
      "sender": "Project owner",
      "timestamp": "2026-07-20 09:15:00",
      "content": "决定先更新FAQ，请内容负责人周五前提交。"
    }
  ]
}
```

### Recognized fields

The normalizer recognizes common aliases:

- text: `content`, `text`, `message`, `msg`, `body`, `message_text`
- message ID: `message_id`, `messageId`, `msg_id`, `msgId`, `localId`, `id`
- sender: `sender`, `sender_name`, `from_name`, `author`, `user`,
  `nickname`, `talker`
- chat: `chat_name`, `group_name`, `conversation`, `room_name`, `chat`
- time: `timestamp`, `time`, `create_time`, `created_at`, `date`
- type: `message_type`, `messageType`, `msg_type`, `type`

Strings are also accepted as messages. Rows previously generated by this Actor
are ignored when a Dataset is reused.

### Privacy controls

Default settings:

- replace participant names with stable within-run labels such as
  `Participant 1`
- redact common email addresses, phone numbers and explicitly labeled WeChat IDs
- exclude common system, notification and media-placeholder rows

Customers may retain supplied names only when authorized. Redaction is a
best-effort pattern screen, not a complete privacy, legal or security review.
Review the delivered evidence before redistributing it.

### Analysis behavior

The Actor uses deterministic lexical cues and exact customer-supplied terms. It
does not claim to use AI and does not invent missing brands, people, decisions
or tasks.

Message labels include:

- question
- purchase or budget signal
- recommendation request
- comparison or alternative
- complaint or service issue
- concern or objection
- decision
- action item or follow-up
- positive feedback or agreement

Discussion dimensions include price, quality, safety, trust, usage, delivery,
support, alternatives, responsibility and time.

### Important limits

- Findings describe only the records supplied to the run.
- Lexical labels can miss implied meaning, irony, slang, voice messages,
  stickers, images and context outside the supplied export.
- Action-item detection does not prove who owns a task or whether it was
  completed.
- Participant activity is not an employee-performance rating.
- Entity reporting covers only exact names supplied in the input.
- Time analysis depends on parseable timestamps and does not infer missing time
  zones.
- This Actor is not legal, compliance, medical, employment or privacy advice.

### Billing

Main event:

`chat-export-insights-report` — **$4.99**

It is triggered once only when the complete report row is written. Row-level
message classifications are then delivered without an additional Dataset-item
event.

# Actor input Schema

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

Run the paid synthetic example, analyze one or more Apify Datasets, or analyze pasted JSON message records.

## `sourceDatasetIds` (type: `array`):

One to ten Apify Dataset IDs containing customer-owned or consented chat export records.

## `uploadedMessages` (type: `array`):

Paste message strings or JSON records. Common message, sender, time, chat and type field aliases are recognized.

## `hasRightToAnalyze` (type: `boolean`):

Required outside demo mode. Confirm that the uploaded or referenced records are customer-owned, consented, authorized, or otherwise lawfully processed.

## `researchTopic` (type: `string`):

Short label for the business question, group, campaign, product, customer cohort, or project being analyzed.

## `messageKeywords` (type: `array`):

Exact words or phrases to count, such as price, delivery, side effects, renewal, product names, project terms, or campaign phrases.

## `knownEntities` (type: `array`):

Exact entity names to measure. The Actor does not claim to automatically discover every brand or person.

## `competitorNames` (type: `array`):

Exact competitor, product, service or alternative names to identify in the supplied messages.

## `customActionTerms` (type: `array`):

Optional exact cues for tasks and follow-ups, such as submit by Friday, assign, owner, deadline, or a team-specific phrase.

## `requireKeywordMatch` (type: `boolean`):

Off by default so surrounding conversation context is preserved. Requires at least one message keyword.

## `privacyMode` (type: `string`):

Anonymize supplied sender names by default or retain them when the customer is authorized to do so.

## `redactContactDetails` (type: `boolean`):

Replaces common email addresses, phone numbers and explicit WeChat-ID labels in output evidence with placeholders.

## `excludeSystemMessages` (type: `boolean`):

Filters common join, leave, recall, notification, image-only and unsupported media placeholder rows.

## `maxMessages` (type: `integer`):

One $4.99 report analyzes at most 2,000 normalized messages across all supplied chats.

## `maxEvidence` (type: `integer`):

Limits auditable excerpts returned in questions, decisions, actions, needs and concerns.

## `conversationWindowSize` (type: `integer`):

Adds nearby messages from the same chat around selected decisions and action items.

## `includeSourceMessages` (type: `boolean`):

Useful for audit and export; turn off for a smaller report row. Row-level output is still delivered.

## Actor input object example

```json
{
  "mode": "demo",
  "sourceDatasetIds": [],
  "uploadedMessages": [],
  "hasRightToAnalyze": false,
  "researchTopic": "WeChat group discussion",
  "messageKeywords": [],
  "knownEntities": [],
  "competitorNames": [],
  "customActionTerms": [],
  "requireKeywordMatch": false,
  "privacyMode": "anonymizeParticipants",
  "redactContactDetails": true,
  "excludeSystemMessages": true,
  "maxMessages": 2000,
  "maxEvidence": 20,
  "conversationWindowSize": 1,
  "includeSourceMessages": true
}
```

# Actor output Schema

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

No description

## `report` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("scrupulous_buckler/wechat-chat-export-analyzer-group-insights-action-items").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("scrupulous_buckler/wechat-chat-export-analyzer-group-insights-action-items").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 '{}' |
apify call scrupulous_buckler/wechat-chat-export-analyzer-group-insights-action-items --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=scrupulous_buckler/wechat-chat-export-analyzer-group-insights-action-items",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "WeChat Chat Export Analyzer — Group Insights & Action Items",
        "description": "Analyze user-provided WeChat chat and group export records for questions, needs, concerns, decisions, action items, supplied brand and competitor mentions, participation patterns, and evidence windows. No WeChat login or chat extraction.",
        "version": "0.1",
        "x-build-id": "s61a4xlqLzos8aez7"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrupulous_buckler~wechat-chat-export-analyzer-group-insights-action-items/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrupulous_buckler-wechat-chat-export-analyzer-group-insights-action-items",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrupulous_buckler~wechat-chat-export-analyzer-group-insights-action-items/runs": {
            "post": {
                "operationId": "runs-sync-scrupulous_buckler-wechat-chat-export-analyzer-group-insights-action-items",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrupulous_buckler~wechat-chat-export-analyzer-group-insights-action-items/run-sync": {
            "post": {
                "operationId": "run-sync-scrupulous_buckler-wechat-chat-export-analyzer-group-insights-action-items",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "properties": {
                    "mode": {
                        "title": "Data source",
                        "enum": [
                            "demo",
                            "datasetMessages",
                            "uploadedMessages"
                        ],
                        "type": "string",
                        "description": "Run the paid synthetic example, analyze one or more Apify Datasets, or analyze pasted JSON message records.",
                        "default": "demo"
                    },
                    "sourceDatasetIds": {
                        "title": "Message Dataset IDs",
                        "type": "array",
                        "description": "One to ten Apify Dataset IDs containing customer-owned or consented chat export records.",
                        "default": [],
                        "items": {
                            "type": "string"
                        }
                    },
                    "uploadedMessages": {
                        "title": "Uploaded message records",
                        "type": "array",
                        "description": "Paste message strings or JSON records. Common message, sender, time, chat and type field aliases are recognized.",
                        "default": []
                    },
                    "hasRightToAnalyze": {
                        "title": "I have the right to analyze this data",
                        "type": "boolean",
                        "description": "Required outside demo mode. Confirm that the uploaded or referenced records are customer-owned, consented, authorized, or otherwise lawfully processed.",
                        "default": false
                    },
                    "researchTopic": {
                        "title": "Research topic",
                        "type": "string",
                        "description": "Short label for the business question, group, campaign, product, customer cohort, or project being analyzed.",
                        "default": "WeChat group discussion"
                    },
                    "messageKeywords": {
                        "title": "Keywords and topics to measure",
                        "type": "array",
                        "description": "Exact words or phrases to count, such as price, delivery, side effects, renewal, product names, project terms, or campaign phrases.",
                        "default": [],
                        "items": {
                            "type": "string"
                        }
                    },
                    "knownEntities": {
                        "title": "Brands, products and other entities",
                        "type": "array",
                        "description": "Exact entity names to measure. The Actor does not claim to automatically discover every brand or person.",
                        "default": [],
                        "items": {
                            "type": "string"
                        }
                    },
                    "competitorNames": {
                        "title": "Competitor and alternative names",
                        "type": "array",
                        "description": "Exact competitor, product, service or alternative names to identify in the supplied messages.",
                        "default": [],
                        "items": {
                            "type": "string"
                        }
                    },
                    "customActionTerms": {
                        "title": "Additional action-item terms",
                        "type": "array",
                        "description": "Optional exact cues for tasks and follow-ups, such as submit by Friday, assign, owner, deadline, or a team-specific phrase.",
                        "default": [],
                        "items": {
                            "type": "string"
                        }
                    },
                    "requireKeywordMatch": {
                        "title": "Analyze only messages matching a supplied keyword",
                        "type": "boolean",
                        "description": "Off by default so surrounding conversation context is preserved. Requires at least one message keyword.",
                        "default": false
                    },
                    "privacyMode": {
                        "title": "Participant-name handling",
                        "enum": [
                            "anonymizeParticipants",
                            "keepSuppliedNames"
                        ],
                        "type": "string",
                        "description": "Anonymize supplied sender names by default or retain them when the customer is authorized to do so.",
                        "default": "anonymizeParticipants"
                    },
                    "redactContactDetails": {
                        "title": "Redact contact details in delivered text",
                        "type": "boolean",
                        "description": "Replaces common email addresses, phone numbers and explicit WeChat-ID labels in output evidence with placeholders.",
                        "default": true
                    },
                    "excludeSystemMessages": {
                        "title": "Exclude system and notification messages",
                        "type": "boolean",
                        "description": "Filters common join, leave, recall, notification, image-only and unsupported media placeholder rows.",
                        "default": true
                    },
                    "maxMessages": {
                        "title": "Messages to analyze (maximum 2,000)",
                        "minimum": 1,
                        "maximum": 2000,
                        "type": "integer",
                        "description": "One $4.99 report analyzes at most 2,000 normalized messages across all supplied chats.",
                        "default": 2000
                    },
                    "maxEvidence": {
                        "title": "Maximum evidence rows per report section",
                        "minimum": 3,
                        "maximum": 100,
                        "type": "integer",
                        "description": "Limits auditable excerpts returned in questions, decisions, actions, needs and concerns.",
                        "default": 20
                    },
                    "conversationWindowSize": {
                        "title": "Messages before and after important evidence",
                        "minimum": 0,
                        "maximum": 3,
                        "type": "integer",
                        "description": "Adds nearby messages from the same chat around selected decisions and action items.",
                        "default": 1
                    },
                    "includeSourceMessages": {
                        "title": "Keep normalized source messages inside the report",
                        "type": "boolean",
                        "description": "Useful for audit and export; turn off for a smaller report row. Row-level output is still delivered.",
                        "default": true
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```