🧪 AI QA Tasks for Quality Engineering 🤖

Welcome to AI QA Tasks! This repository provides a collection of markdown files designed to supercharge your quality assurance workflow with AI-powered IDEs and CLIs. Originally inspired by snarktank/ai-dev-tasks, these tools work with any AI coding assistant including Cursor, Claude Code, Windsurf, and others.

By leveraging these structured prompts, you can systematically approach quality engineering from requirements analysis to comprehensive test automation, with built-in checkpoints for verification. Stop wrestling with ad-hoc testing approaches and start guiding your AI collaborator through structured QA processes!

✨ The Core QA Philosophy

Building comprehensive test coverage with AI can sometimes feel overwhelming. This workflow brings structure, clarity, and control to the QA process by:

1. Requirements Analysis: Converting PRDs, stories, and tickets into testable requirements
2. Test Strategy Planning: Creating comprehensive test plans covering all testing types
3. Systematic Test Creation: Generating unit, integration, API, performance, and E2E tests
4. Coverage & Metrics: Ensuring measurable quality gates and reporting
5. Framework Integration: Adapting tests to your specific tech stack and tooling

🎯 Workflow: From Requirements to Comprehensive Testing

Here's the step-by-step process using the .md files in this repository:

1️⃣ Create Test Requirements Document (TRD) from Requirements

Whether you have a PRD, Azure DevOps story, JIRA ticket, or other requirements, convert them into testable requirements:

Use @create-trd-md.md
Here's the requirement document I want to analyze for testing: [Paste your PRD/Story/Ticket]
Tech stack: [Your stack - e.g., React, Node.js, PostgreSQL]
Current testing tools: [Your current setup - e.g., Jest, Cypress, Playwright]

2️⃣ Generate Comprehensive Test Strategy

Transform your TRD into a detailed test strategy covering all testing types:

Use @generate-test-strategy-md.md with @[your-trd-file].md
Focus areas: [unit, integration, api, performance, e2e, accessibility, security]

3️⃣ Create Test Implementation Plan

Break down your test strategy into actionable tasks:

Use @generate-test-tasks-md.md with @[your-test-strategy-file].md

4️⃣ Implement Tests Systematically

Execute your test plan step by step:

Use @implement-test-task-md.md
Current task: [Reference specific task from your test plan]

5️⃣ Generate Test Coverage & Metrics Reports

Track and report on your testing progress:

Use @generate-test-report-md.md
Test results directory: [path to your test results]
Coverage requirements: [your coverage thresholds]

📁 Repository Structure

/ai-qa-tasks/
├── README.md                         # This file
├── create-trd-md.md                  # Convert requirements to Test Requirements Document
├── generate-test-strategy-md.md      # Create comprehensive test strategy
├── generate-test-tasks-md.md         # Break strategy into implementation tasks
├── implement-test-task-md.md         # Execute individual test tasks
├── generate-test-report-md.md        # Create coverage and metrics reports
├── quick-start-guide.md
├── contributing-guide.md
├── examples/                         # Example outputs
│   ├── sample-trd-example.md
│   ├── sample-test-strategy.md
│   └── microservices-testing.md
├── templates/                        # Reusable templates
│   ├── api-test-template.md
│   ├── e2e-test-template.md
│   ├── performance-test-template.md
│   └── bug-report-template.md
└── docs/
    ├── best-practices.md
    └── troubleshooting.md

🌟 Benefits

• Comprehensive Coverage: Ensures all testing types are considered and planned
• Requirements Traceability: Links tests back to original requirements
• Framework Agnostic: Adapts to your specific tech stack and testing tools
• Measurable Quality: Built-in metrics and coverage tracking
• Systematic Approach: Prevents ad-hoc testing and ensures consistency
• AI-Guided Implementation: Step-by-step guidance for test creation
• Documentation First: Creates maintainable test documentation

🛠️ How to Use

For Cursor Users

1. Clone or Download: Get these .md files into your project or a central location where Cursor can access them
2. Follow the Workflow: Systematically use the .md files in Cursor's Agent chat as described in the 5-step workflow above
3. Adapt and Iterate: Modify the prompts to suit your specific testing needs and standards

For Claude Code Users

1. Copy files to your repo: Copy the .md files to a subdirectory in your project (e.g., /ai-qa-tasks)
2. Reference in project docs: Add these lines to your project's documentation:

# AI QA Tasks
Use these files when I request structured QA assistance:
- @ai-qa-tasks/create-trd.md
- @ai-qa-tasks/generate-test-strategy.md
- @ai-qa-tasks/generate-test-tasks.md
- @ai-qa-tasks/implement-test-task.md
- @ai-qa-tasks/generate-test-report.md

💡 Tips for QA Success

• Be Specific About Requirements: The more context you provide about your application and testing needs, the better the AI's output
• Include Your Tech Stack: Always specify your testing frameworks, tools, and infrastructure
• Define Quality Gates: Set clear coverage thresholds and quality metrics upfront
• Iterate on Test Design: Review and refine test approaches before implementing
• Consider All Test Types: Don't skip any testing layer - each serves a purpose
• Plan for Maintenance: Structure tests for long-term maintainability

🎯 Testing Types Covered

• Unit Tests: Component and function-level testing
• Integration Tests: Module and service integration testing
• API Tests: REST/GraphQL endpoint testing
• Performance Tests: Load, stress, and performance benchmarking
• End-to-End Tests: Full user journey testing
• Accessibility Tests: WCAG compliance and usability testing
• Security Tests: Vulnerability and penetration testing
• Visual Regression Tests: UI consistency testing

🔧 Supported Tech Stacks & Tools

The templates and prompts are designed to work with popular testing frameworks:

Frontend: Jest, Vitest, React Testing Library, Vue Test Utils, Cypress, Playwright, WebdriverIO

Backend: Jest, Mocha, Chai, Supertest, Newman, Artillery, K6

Mobile: Detox, Appium, XCTest, Espresso

API: Postman, Insomnia, REST Assured, Karate

Performance: K6, Artillery, JMeter, Lighthouse

Visual: Percy, Chromatic, BackstopJS

📊 Quality Metrics & Reporting

Each workflow includes generation of:

• Test coverage reports (line, branch, function coverage)
• Test execution summaries
• Performance benchmarks
• Accessibility audit results
• Security scan reports
• Traceability matrices (requirements to tests)

🤝 Contributing

Got ideas to improve these QA workflows or have new testing approaches? Contributions welcome!

• Open an issue to discuss changes or suggest new testing strategies
• Submit a pull request with your enhancements
• Share examples of successful QA implementations

📚 Additional Resources

• Testing Best Practices
• Test Pyramid Concept
• Accessibility Testing Guide
• OWASP API Security Top 10

✅ Validation and CI

Use the local script to mirror CI checks before pushing changes.

• Local validation (Windows/PowerShell)

./scripts/validate.ps1 -Strict -FailOnLinkIssues

• CI workflow: /.github/workflows/validate.yml

  • Markdown linting (non-blocking; honors .markdownlint.json)
  • Markdown link check (continues on error; uses .github/markdown-link-check-config.json when present)
  • Spell check via crate-ci/typos (uses .github/typos.toml when present)
  • Examples validation for code completeness in examples/ and templates/
  • Repository stats generation on main only (STATS.md)

• Config files (optional but supported):

  • .markdownlint.json
  • .github/markdown-link-check-config.json
  • .github/typos.toml

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This structured approach helps ensure comprehensive test coverage, maintains quality standards, and creates a reliable foundation for continuous integration and deployment.