[Meetup] AI skills for QA that get you hired: Solo task

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These are tests created for end to end testing of given application using given template

working fine for me.

Worked for me
 

feature: add complete Playwright login test suite with POM architecture for Login page

• Implement Page Object Model (POM) with robust locator strategies
• Add comprehensive test coverage for happy path, negative, edge cases, and security scenarios
• Configure multi-browser testing (Chromium, Firefox, WebKit) with CI/CD integration
• Include TypeScript strict mode, environment variables for credentials, and detailed documentation
• Set up GitHub Actions workflow for automated testing with artifact uploads

Test scenarios covered:

• Successful login with valid credentials (@smoke @regression)
• Failed login with invalid password/email (@regression)
• Empty/partial form submissions (@regression)
• SQL injection and XSS attack prevention (@security)
• Login after session expiry/logout (@regression)

Files added:

• playwright.config.ts: Multi-browser config with retries and reporting
• pages/LoginPage.ts: POM class with encapsulated actions and getters
• tests/fixtures.ts: Extended test fixtures with cleanup
• tests/login.spec.ts: 11 comprehensive test scenarios
• .github/workflows/ci.yml: GitHub Actions CI/CD pipeline
• README.md: Complete documentation and usage guide

All TypeScript files compile successfully with strict mode enabled.

Here is the solo activity result

EAEmployeeWithTestSprite/tests at ajitesh/solo-group-activity-ans · ajitesh11/EAEmployeeWithTestSprite

And here is the group activity result

EAEmployeeWithTestSprite/GROUP_ACTIVITY/agents at ajitesh/solo-group-activity-ans · ajitesh11/EAEmployeeWithTestSprite

Hello Team,
Solo Activity Submission – AI Testing Agents Orchestration

• 📁 Implementation Repository:
  End-to-end solution showcasing multi-agent orchestration (Playwright, API, BDD) with scalable design and CI-ready structure:
  👉 https://github.com/SriniCh1980/shiftsync-solo-activity/tree/main/SOLO_ACTIVITY
• 📊 Execution Results (Playwright Report):
  Detailed test execution report with UI validation insights and run metrics:
  👉 https://github.com/SriniCh1980/shiftsync-solo-activity/blob/main/SOLO_ACTIVITY/tests/playwright_test_results.html

Solo task submission.
I have added respective tests and now I am giving link to repo

https://github.com/aarti-kulkarni-5393/solo_task.git

I have uploaded all tests here

UI Tests:

API Tests:

🚀 Agentic Test Automation: Building a Production-Ready Playwright Suite

I have completed a comprehensive test automation project exploring the intersection of AI agents and software quality. Using a custom AI skill (playwright-tester.agent.md), I architected and generated a complete, production-grade Playwright End-to-End (E2E) test suite for a React/Node.js Employee Manager application.

This project serves as a real-world deliverable demonstrating how AI-driven workflows can accelerate the creation of robust, non-flaky test infrastructure.

✨ Key Highlights:

• Comprehensive Coverage: 197 tests spanning across 5 browser projects (Desktop & Mobile).

  

   

• Zero Flakiness: Achieved a 100% pass rate by prioritizing role-based locators and auto-waiting mechanisms over brittle CSS selectors.

• Modern Architecture: Fully implemented the Page Object Model (POM) for maximum maintainability.

• Advanced Playwright Features: Successfully integrated isolated API mocking (page.route()) and pixel-perfect Visual Regression testing.

• CI/CD Ready: Fully integrated with GitHub Actions for automated execution, health-checking, and artifact retention (traces/videos on failure).

By acting as a "Senior QA Automation Engineer," the AI agent guided the exploration phase, test design, flakiness debugging, and CI pipeline setup from start to finish.

🔗 Check out the code: GitHub Repository 📄 Deep dive into the methodology: [Read the attached PDF for the full Project Report]

 Agentic Playwright Test Suite with Live CI Report

Built a production-ready Playwright E2E test suite for the Employee Manager app, driven by a custom AI agent with a SKILL.md domain knowledge file that encodes application-specific selectors, reusable helpers, and known pitfalls.
 

✨ What was built:

45 tests across 4 spec files covering every user journey: authentication (all 3 users), employee CRUD with API seeding, real-time search, navigation & route guards
SKILL.md — a reusable domain knowledge capsule containing the full selector reference, loginAs/seed/clearAll helper patterns, and a pitfall table (e.g., MUI empty state always renders a row — you can never use toHaveCount(0))
100% pass rate — zero flakiness achieved by isolating each test with API seeding and scoping ambiguous selectors to dialogs

GitHub Actions CI — automated on every push, publishes Playwright HTML report to GitHub Pages
📊 Live report: https://gauravkhuraana.github.io/ActivityAI/solo/

🔗 Repository: https://github.com/gauravkhuraana/ActivityAI

Checkout the readme file 

Key architectural decisions:

1. API seeding (POST /employees) before each test — no UI setup, true test isolation
2. Scoped delete dialog button (dialog.getByRole('button', { name: 'Delete' })) — avoids row/dialog button ambiguity
3. Text-based empty state assertion (getByText('No employees found.')) — robust against MUI's always-present <TableRow>

Thanks to Tricentis for organizing such great events and inviting experts like Karthik and these challenges are icing on the cake

Thank you