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Playwright Expert

CommunityPopular
Jeffallan
playwright-expert

Use when writing E2E tests with Playwright, setting up test infrastructure, or debugging flaky browser tests. Invoke to write test scripts, create page objects, configure test fixtures, set up reporters, add CI integration, implement API mocking, or perform visual regression testing. Trigger terms: Playwright, E2E test, end-to-end, browser testing, automation, UI testing, visual testing, Page Object Model, test flakiness.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill nameplaywright-expert
Stars
11.5K
Forks
1.1K
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Jeffallan on GitHub. Read the source before you install it.

Installation

Install the Playwright Expert AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/playwright-expert .claude/skills/playwright-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Playwright Expert in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Playwright Expert on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Playwright Expert is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Playwright Expert

E2E testing specialist with deep expertise in Playwright for robust, maintainable browser automation.

Core Workflow

  1. Analyze requirements - Identify user flows to test
  2. Setup - Configure Playwright with proper settings
  3. Write tests - Use POM pattern, proper selectors, auto-waiting
  4. Debug - Run test → check trace → identify issue → fix → verify fix
  5. Integrate - Add to CI/CD pipeline

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Selectorsreferences/selectors-locators.mdWriting selectors, locator priority
Page Objectsreferences/page-object-model.mdPOM patterns, fixtures
API Mockingreferences/api-mocking.mdRoute interception, mocking
Configurationreferences/configuration.mdplaywright.config.ts setup
Debuggingreferences/debugging-flaky.mdFlaky tests, trace viewer

Constraints

MUST DO

  • Use role-based selectors when possible
  • Leverage auto-waiting (don't add arbitrary timeouts)
  • Keep tests independent (no shared state)
  • Use Page Object Model for maintainability
  • Enable traces/screenshots for debugging
  • Run tests in parallel

MUST NOT DO

  • Use waitForTimeout() (use proper waits)
  • Rely on CSS class selectors (brittle)
  • Share state between tests
  • Ignore flaky tests
  • Use first(), nth() without good reason

Code Examples

Selector: Role-based (correct) vs CSS class (brittle)

typescript
// ✅ Role-based selector — resilient to styling changes
await page.getByRole('button', { name: 'Submit' }).click();
await page.getByLabel('Email address').fill('user@example.com');

// ❌ CSS class selector — breaks on refactor
await page.locator('.btn-primary.submit-btn').click();
await page.locator('.email-input').fill('user@example.com');

Page Object Model + Test File

typescript
// pages/LoginPage.ts
import { type Page, type Locator } from '@playwright/test';

export class LoginPage {
  readonly page: Page;
  readonly emailInput: Locator;
  readonly passwordInput: Locator;
  readonly submitButton: Locator;
  readonly errorMessage: Locator;

  constructor(page: Page) {
    this.page = page;
    this.emailInput = page.getByLabel('Email address');
    this.passwordInput = page.getByLabel('Password');
    this.submitButton = page.getByRole('button', { name: 'Sign in' });
    this.errorMessage = page.getByRole('alert');
  }

  async goto() {
    await this.page.goto('/login');
  }

  async login(email: string, password: string) {
    await this.emailInput.fill(email);
    await this.passwordInput.fill(password);
    await this.submitButton.click();
  }
}
typescript
// tests/login.spec.ts
import { test, expect } from '@playwright/test';
import { LoginPage } from '../pages/LoginPage';

test.describe('Login', () => {
  let loginPage: LoginPage;

  test.beforeEach(async ({ page }) => {
    loginPage = new LoginPage(page);
    await loginPage.goto();
  });

  test('successful login redirects to dashboard', async ({ page }) => {
    await loginPage.login('user@example.com', 'correct-password');
    await expect(page).toHaveURL('/dashboard');
  });

  test('invalid credentials shows error', async () => {
    await loginPage.login('user@example.com', 'wrong-password');
    await expect(loginPage.errorMessage).toBeVisible();
    await expect(loginPage.errorMessage).toContainText('Invalid credentials');
  });
});

Debugging Workflow for Flaky Tests

typescript
// 1. Run failing test with trace enabled
// playwright.config.ts
use: {
  trace: 'on-first-retry',
  screenshot: 'only-on-failure',
}

// 2. Re-run with retries to capture trace
// npx playwright test --retries=2

// 3. Open trace viewer to inspect timeline
// npx playwright show-trace test-results/.../trace.zip

// 4. Common fix — replace arbitrary timeout with proper wait
// ❌ Flaky
await page.waitForTimeout(2000);
await page.getByRole('button', { name: 'Save' }).click();

// ✅ Reliable — waits for element state
await page.getByRole('button', { name: 'Save' }).waitFor({ state: 'visible' });
await page.getByRole('button', { name: 'Save' }).click();

// 5. Verify fix — run test 10x to confirm stability
// npx playwright test --repeat-each=10

Output Templates

When implementing Playwright tests, provide:

  1. Page Object classes
  2. Test files with proper assertions
  3. Fixture setup if needed
  4. Configuration recommendations

Knowledge Reference

Playwright, Page Object Model, auto-waiting, locators, fixtures, API mocking, trace viewer, visual comparisons, parallel execution, CI/CD integration

Documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Playwright Expert AI skill do?

Use when writing E2E tests with Playwright, setting up test infrastructure, or debugging flaky browser tests. Invoke to write test scripts, create page objects, configure test fixtures, set up reporters, add CI integration, implement API mocking, or perform visual regression testing. Trigger terms: Playwright, E2E test, end-to-end, browser testing, automation, UI testing, visual testing, Page Object Model, test flakiness.

Why use Playwright Expert on TypingMind?

Because you install it once and use it with any model. Playwright Expert is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Playwright Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/playwright-expert. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Playwright Expert?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Playwright Expert?

As many as you like. As long as a model supports skills, you can use Playwright Expert with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Playwright Expert AI skill free?

Yes. It is published on GitHub by Jeffallan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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