# PAL | Product Review Schema Checker (`practical_ai_lab_jp/pal-review-schema-auditor`) Actor

Audit published Review JSON-LD for author, rating and reviewed item. Export structured QA findings. Try the public Example task first; replace sample URLs with your own. Static HTML only.

- **URL**: https://apify.com/practical_ai_lab_jp/pal-review-schema-auditor.md
- **Developed by:** [Practical AI Lab](https://apify.com/practical_ai_lab_jp) (community)
- **Categories:** E-commerce, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 completed review markup audits

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## PAL Review Markup Audit

**Demo transparency:** the prefilled public Apify-hosted HTML is a **synthetic PAL test fixture**. It contains no real product reviews, stock assertions, marketing campaign performance or customer data. Replace the sample with your own public HTTPS URLs for production checks.

### Start here: check product review structured-data presence

**For ecommerce catalog teams and SEO QA:** when you migrate product templates, you may need to verify that publicly published Review JSON-LD remains present and parseable. This Actor identifies Review nodes in static page metadata and exports up to 20 author/rating summaries per audited page.

Example input:

```json
{"urls":["https://api.apify.com/v2/key-value-stores/DHMHtotPcN9CAKXYj/records/complete.html"]}
```

Open the Dataset and inspect `details.reviewCount`, `details.reviewSummaries` and `issues`. A result containing `review_schema_missing` simply reports no Review JSON-LD found in the static HTML; it does **not** prove the site has no customer reviews. The synthetic demo includes one fictional Review JSON-LD node so the review count is visible. Use your own public product URLs to check actual published reviews.

**Billing/fit:** a successful public page check is a priced event as listed on the Apify Pricing tab. This does not fabricate reviews, evaluate rating authenticity, read JavaScript-rendered reviews or guarantee rich results in search.

**Related PAL:** [product listing QA](https://apify.com/practical_ai_lab_jp/pal-product-stock-schema-check) and [rating schema inspection](https://apify.com/practical_ai_lab_jp/pal-aggregate-rating-checker) are separate tools.

Inspect Review schema blocks for author, rating and reviewed item.

### Ideal users and practical workflow

**Best for:** ecommerce operators, product-catalog teams and merchandising analysts.

**What it checks:** Inspect Review schema blocks for author, rating and reviewed item. Upload a short list of public HTTPS URLs to receive an individual evidence-based record and issue flags per page. Review the flagged URLs first, then export the Dataset as JSON or CSV for your team's workflow.

**When it is useful:** When product feeds change, before a catalog launch, or after price and availability updates.

**What it does not do:** It does not crawl an entire website automatically, render JavaScript, guarantee a search ranking, or change the target site. Check the exact limitations below before purchasing runs.

### Why use this PAL Actor?

Get a structured, repeatable report for this specific issue without opening dozens of webpages by hand. Each input URL is analyzed independently. The output identifies data found on the page and flags likely omissions for manual review. Save output in Apify Dataset and export to JSON, CSV or Excel.

### Practical use cases

**Built for:** ecommerce operators, catalog managers and SEO consultants.

- **Spot the issue:** Inspect Review schema blocks for author, rating and reviewed item. See machine-readable results for each submitted public URL.
- **Prioritize corrections:** use `issues`, `issueCount` and `details` to decide which pages merit human review.
- **Repeat as needed:** rerun the same URL list after editing page markup to compare findings.

### What makes this tool useful?

Focused on **Review Markup Audit**, rather than requiring a full-site crawling subscription. Export results to a spreadsheet, CSV or a data pipeline; connect via Apify API where appropriate. The tool processes static HTML and embedded metadata, with no client-side browser, API keys or private-page logins.

**Important:** each URL is a separate charged successful audit event at the rate visible in Apify Store. A missing signal is an observation, not a legal or search-engine verdict. If your site renders important data only with JavaScript, that data may not appear in the result.

### How this fits with other Practical AI Lab (PAL) tools

For ecommerce projects, start with [PAL Product Price & Stock Snapshot](https://apify.com/practical_ai_lab_jp/my-actor) and follow with [PAL Product GTIN & SKU SEO Auditor](https://apify.com/practical_ai_lab_jp/my-actor-3) to inspect identifiers. For storefront trust information, use [PAL Store Policy Link Mapper](https://apify.com/practical_ai_lab_jp/my-actor-4) before reviewing [return](https://apify.com/practical_ai_lab_jp/my-actor-1) or [shipping](https://apify.com/practical_ai_lab_jp/my-actor-2) schema. These are independent PAL tools; there is **no bundle requirement**.

### Example input

```json
{"urls": ["https://api.apify.com/v2/key-value-stores/DHMHtotPcN9CAKXYj/records/complete.html"]}
```

### Results

Each successful fetch produces a Dataset row with `sourceUrl`, `finalUrl`, `mode`, `issueCount`, `issues` and `details`. Issue flags indicate markup detected in *static HTML*; they are not a guarantee of legal compliance, accessibility certification, search rank, or a live inventory position. Missing data can be published through JavaScript or other channels not read here.

### Billing

Pay per event: **`pal-review`** is triggered for each successfully fetched and audited page at the price displayed by Apify Store. URL errors generate a free error row. Maximum 18 URLs per run. No paid API keys, logins, or third-party services required.

### Technical limits

Public HTTPS only; no JavaScript rendering, captcha bypass or private pages. Each response is at most 1.5 MB, 11-second network timeout. The site may block bots. Output reflects visible HTML at retrieval time, not a complete website audit. Running the Actor does not itself fix issues.

### More Practical AI Lab (PAL) tools

Use independent PAL tools in a natural sequence: first capture price and stock, then audit the corresponding product markup; or locate policy links and inspect returns/shipping markup. Each Actor is separately usable, with no mandatory bundle.

- [PAL Product Price & Stock Snapshot](https://apify.com/practical_ai_lab_jp/my-actor)
- [PAL Return Policy Schema Auditor](https://apify.com/practical_ai_lab_jp/my-actor-1)
- [PAL Shipping Promise Schema Audit](https://apify.com/practical_ai_lab_jp/my-actor-2)
- [PAL Product GTIN & SKU SEO Auditor](https://apify.com/practical_ai_lab_jp/my-actor-3)
- [PAL Store Policy Link Mapper](https://apify.com/practical_ai_lab_jp/my-actor-4)

Browse the [PAL developer profile](https://apify.com/practical_ai_lab_jp) for additional focused audit tools.

***

Practical AI Lab | Catalog product 38 | ECOM

# Actor input Schema

## `urls` (type: `array`):

The prefilled link is a public PAL-created SYNTHETIC test page, not a real store. Replace it with your own HTTPS pages for real analysis. Static HTML only.

## Actor input object example

```json
{
  "urls": [
    "https://api.apify.com/v2/key-value-stores/DHMHtotPcN9CAKXYj/records/complete.html"
  ]
}
```

# Actor output Schema

## `dataset` (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 = {
    "urls": [
        "https://api.apify.com/v2/key-value-stores/DHMHtotPcN9CAKXYj/records/complete.html"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("practical_ai_lab_jp/pal-review-schema-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 = { "urls": ["https://api.apify.com/v2/key-value-stores/DHMHtotPcN9CAKXYj/records/complete.html"] }

# Run the Actor and wait for it to finish
run = client.actor("practical_ai_lab_jp/pal-review-schema-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 '{
  "urls": [
    "https://api.apify.com/v2/key-value-stores/DHMHtotPcN9CAKXYj/records/complete.html"
  ]
}' |
apify call practical_ai_lab_jp/pal-review-schema-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,practical_ai_lab_jp/pal-review-schema-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/tks6659GypKqfyKMp/builds/Spf9tFoURsH4wQ3uk/openapi.json