# PAL Title Tag Audit (`practical_ai_lab_jp/my-actor-11`) Actor

Inspect HTML title length and identify missing, empty or overlong page titles.

- **URL**: https://apify.com/practical_ai_lab_jp/my-actor-11.md
- **Developed by:** [Practical AI Lab](https://apify.com/practical_ai_lab_jp) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 title tag 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 Title Tag Audit

Inspect HTML title length and identify missing, empty or overlong page titles.

### 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.

### Example input

```json
{"urls": ["https://scrapeme.live/shop/Pikachu/"]}
```

### 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-title`** 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 01 | SEO

# Actor input Schema

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

Each URL yields an independent audit row. Static HTML only. No authentication.

## Actor input object example

```json
{
  "urls": [
    "https://scrapeme.live/shop/Pikachu/"
  ]
}
```

# 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://scrapeme.live/shop/Pikachu/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("practical_ai_lab_jp/my-actor-11").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://scrapeme.live/shop/Pikachu/"] }

# Run the Actor and wait for it to finish
run = client.actor("practical_ai_lab_jp/my-actor-11").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://scrapeme.live/shop/Pikachu/"
  ]
}' |
apify call practical_ai_lab_jp/my-actor-11 --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,practical_ai_lab_jp/my-actor-11"
        }
    }
}
```

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/dvhJ2YVADjbBeoKbP/builds/GmmocWaK7IztEAuHO/openapi.json