# Review Dataset Auditor (`agentworkflowlab/review-dataset-auditor`) Actor

Audit review Datasets for completeness, malformed fields, duplicate IDs, and duplicate content.

- **URL**: https://apify.com/agentworkflowlab/review-dataset-auditor.md
- **Developed by:** [Agent Workflow Lab](https://apify.com/agentworkflowlab) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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/actors/running/actors-in-store.md#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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Review Dataset Auditor

Audit heterogeneous review records before analytics, triage, or response workflows. The Actor produces one deterministic report covering usable review text, rating/date/author completeness, duplicate IDs, and exact normalized-text duplicates across common Google Maps, Amazon, App Store, and generic review fields.

No external API key or LLM is required. The Actor makes no external model or third-party API calls.

### Input

Use the **Source Dataset** READ-only resource picker, pass reviews inline, or run `{}` for a clearly labeled embedded sample. Input precedence is: presence of `reviews` (including `[]`), then nonblank `datasetId`, then sample.

```json
{
  "datasetLabel": "May review export",
  "reviews": [
    { "id": "r-1", "text": "Exports fail every afternoon.", "rating": 2, "date": "2026-05-01" },
    { "id": "r-1", "text": "Exports fail every afternoon.", "rating": 2, "date": "2026-05-01" }
  ],
  "maxDuplicateGroups": 25
}
```

### Output and pricing shape

Every run writes exactly one `review_dataset_audit_report` Dataset item and the same report to `OUTPUT`. One aggregate audit equals one Dataset result. Synthetic Dataset-item charging is automatic; the code contains no manual charging.

The quality score is a bounded deterministic readiness indicator, not a fraud or authenticity score. Exact duplicate content is matched only after lowercasing and whitespace normalization; semantic near-duplicates are not inferred.

### Limits and privacy

- At most 5,000 source records and 100 returned duplicate groups.
- Review text is inspected through the tested Review Intelligence normalization boundary; no raw review body is copied into duplicate-group output.
- Source Dataset access is READ-only and never writes to or deletes the source.
- User data is written only to the run's default Dataset and `OUTPUT`; Apify retention settings apply.

# Actor input Schema

## `reviews` (type: `array`):

Inline review records. Common Google Maps, Amazon, App Store, and generic review aliases are inspected. Maximum 5,000 records.

## `datasetId` (type: `string`):

READ-only source Dataset, used only when reviews is absent.

## `datasetLabel` (type: `string`):

Optional human-readable label for the audited Dataset.

## `maxDuplicateGroups` (type: `integer`):

Maximum exact duplicate-content groups included in the single report.

## `maxReviews` (type: `integer`):

Maximum source records to inspect; hard-capped at 5,000.

## Actor input object example

```json
{
  "maxDuplicateGroups": 25,
  "maxReviews": 1000
}
```

# Actor output Schema

## `reports` (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("agentworkflowlab/review-dataset-auditor").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("agentworkflowlab/review-dataset-auditor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 agentworkflowlab/review-dataset-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentworkflowlab/review-dataset-auditor"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/teyIFyHaO4ucaEWIH/builds/k8g3GQW1eSpgJGh8N/openapi.json