# The Artifact Machine Mobile UX Auditor (`artifact-machine/artifact-machine-mobile-ux-auditor`) Actor

Check touch targets, viewport, font sizes, and mobile usability.

- **URL**: https://apify.com/artifact-machine/artifact-machine-mobile-ux-auditor.md
- **Developed by:** [The Artifact Machine](https://apify.com/artifact-machine) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / mobile ux audit 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.

- **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

## The Artifact Machine Mobile UX Auditor

A small artifact for auditing mobile user experience — viewport meta, touch targets, horizontal scroll, font sizes, and mobile interaction patterns. Uses Playwright to render the page at mobile viewport dimensions and extract UX metrics.

Use this Actor before a mobile launch, after responsive redesigns, or as part of ongoing mobile quality monitoring. It renders the page in a headless Chromium browser at 412x915 viewport (Pixel-like) and analyzes touch target compliance, scroll behavior, and mobile-friendly patterns.

Pulled from The Artifact Machine: generated, tested, and cleaned up by a human.

### What It Checks

- **Viewport meta**: presence, width=device-width, initial-scale, zoom disabled
- **Touch targets**: interactive elements below 44x44px minimum, elements too close together
- **Horizontal scroll**: content wider than viewport, overflow-causing elements
- **Text readability**: body font size (recommended 14px+ for mobile)
- **Mobile patterns**: responsive images, sticky headers, mobile-optimized inputs, autocomplete hints
- **Autoplay media**: video/audio with autoplay without muted attribute

### Best For

- mobile UX quality audits
- responsive design verification
- WCAG 2.5.8 Target Size compliance
- pre-launch mobile checklist
- agency mobile UX reports

### Input

```json
{
  "url": "https://example.com",
  "timeoutMs": 30000
}
```

#### Input Fields

- `url`: public page URL to audit.
- `timeoutMs`: maximum navigation time in milliseconds (5000-60000, default 30000).

### Output

The Actor writes one dataset item and an `OUTPUT` key-value record with:

- composite mobile UX score
- viewport subscores (presence, device-width, zoom)
- touch target subscores (total, too small, too close)
- scrolling subscores (horizontal scroll, overflow elements)
- mobile pattern subscores (font size, responsive images, sticky headers, inputs)
- array of detected issues with severity, descriptions, and fix guidance

### Limits

- This Actor audits one submitted page.
- Touch targets are sampled from the first 300 interactive elements.
- The viewport is fixed at 412x915 (Pixel-like) for mobile simulation.
- Some mobile patterns (actual touch events, gesture handling) cannot be detected via DOM inspection alone.
- No external API keys required.

### Pricing

Use pay-per-event pricing based on completed audits. Suggested starting price: `$1.00` to `$3.00` per completed mobile UX report after private runtime cost is measured.

# Actor input Schema

## `url` (type: `string`):

The public webpage to audit. If no scheme is provided, https:// is assumed.

## `timeoutMs` (type: `integer`):

Maximum page navigation time in milliseconds.

## Actor input object example

```json
{
  "url": "https://example.com",
  "timeoutMs": 30000
}
```

# Actor output Schema

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

Default dataset items. Each item contains the target URL, viewport/touch/scroll/pattern scores, and detected issues.

## `summary` (type: `string`):

The same single-run summary stored as the OUTPUT key-value record.

# 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 = {
    "url": "https://example.com"
};

// Run the Actor and wait for it to finish
const run = await client.actor("artifact-machine/artifact-machine-mobile-ux-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 = { "url": "https://example.com" }

# Run the Actor and wait for it to finish
run = client.actor("artifact-machine/artifact-machine-mobile-ux-auditor").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 '{
  "url": "https://example.com"
}' |
apify call artifact-machine/artifact-machine-mobile-ux-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=artifact-machine/artifact-machine-mobile-ux-auditor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/lW758HWowrEYNYJRc/builds/wbRTOFkrZqXUT14YX/openapi.json