🤖 AI-Native QA Automation Platform

Built an AI-powered QA automation platform using Claude Code multi-agent orchestration — 4 specialized skill agents (scenario generation, test strategy, test generation, code review) that read domain knowledge, live source code, and business rules before producing output; generated 53 test scenarios stratified across a proper test pyramid (unit / API / component / E2E) for a full-stack Next.js + Express + MySQL application.

Built by Snehal Patil · Senior SDET / AI-Native QA Automation Engineer

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Business Impact

• Reduced manual test design effort by using specialized AI agents to generate scenarios, assign the right test layer, and produce executable tests.
• Improved test relevance by grounding generation in business rules, live source code, UI selectors, API contracts, and existing tests.
• Enforced a healthy test pyramid by distributing coverage across unit, API, component, and E2E layers instead of overloading UI tests.
• Increased confidence in critical workflows such as authentication, booking rules, seat allocation, and cross-user security through specification-driven validation.

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What is this?

Most AI-assisted testing tools generate generic tests in isolation. This project is different.

EventHub is a production-quality ticket booking application used as a live system under test. On top of it sits a Claude Code multi-agent QA framework where 4 specialized AI agents collaborate in sequence — each reading domain knowledge, business rules, and actual source code before producing any output.

The result: structured test scenarios, a rationalized test pyramid, self-validating Playwright tests, and AI-driven code review — all grounded in real application behavior, not guesswork.

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The 4 agents

.claude/skills/
├── create-scenarios/    AI Functional Tester    — generates 53 scenarios across 6 thinking lenses
├── test-strategy/       AI Test Architect       — assigns pyramid layers with source-traced rationale
├── generate-tests/      AI Test Engineer        — writes, runs, diagnoses, and fixes Playwright tests
└── review-tests/        AI Code Reviewer        — audits tests against standards, selectors, domain rules

Agent pipeline

/create-scenarios 
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         ▼
  docs/test-scenarios.md        53 scenarios · 6 categories · traced to business rules
         │
         ▼
/test-strategy 
         │
         ▼
  docs/test-strategy.md         layer assignments · rationale · anti-pattern flags
         │
         ▼
/generate-tests 
         │
         ├── reads domain knowledge + source code
         ├── writes test file
         ├── runs tests in real browser (Playwright MCP)
         ├── diagnoses failures: error message + live DOM + source code
         └── fixes and re-runs until green
         │
         ▼
/review-tests 
         │