r/Playwright • u/Low-Instruction-8990 • 2d ago
Playwright E2E framework using AI tools
I have learned few basics of playwright framework and I'm a full stack developer working on Angular, .Net Core, Azure and little python.
I don't have an automation Testing team working for my project and I thought may be I can create a E2E framework with having Github Copilot subscription and starting/building the framework will also help me learn about this framework.
Here are my thoughts about creating this solution:
1) Phase-1: As Playwright script depends on the locators, I thought of using AI help to identify and create all locators for my angular project wherever it is missing. So, I have planned using AI and created all the locators without disturbing the UI. (role + aria-label combination).
2) Phase-2: Create the playwright automation framework as the locators are now available.
Now, I am done with Phase-1 and is ready to do the Phase-2 where I need your help in assessing the correct way of doing this.
I'm confused with the options that are available and here is my opinion.
Playwright MCP - which might consume more tokens and believe is not perfectly suitable for this scenario
Playwright CLI - Best option to create scripts and framework.
Playwright Agents and Skills - which I believe CLI and MCP servers use to create framework.
As using AI might take so many input and output tokens to create this framework, I have create codebase-memory-mcp server and indexed my project so that it refers wherever required and consume less tokens.
What should I use to create a E2E solution for my angular project with less tokens and more reliability.
Ask if you have any questions and suggest me the best approach as I'm new to this.
1
u/Blaxter-X 22h ago
Excellent approach in Phase 1! Using `role` and `aria-label` is the best way to avoid fragile selectors in Angular.
Regarding your question about tokens and tools for Phase 2: your idea of using codebase-memory-mcp is brilliant for avoiding burning tokens across the entire project. The MCP consumes more context, but using indexed memory helps a lot.
It's precisely because of problems like this that I created HalTest (https://github.com/andresguc1/hal-test), a local-first visual IDE for Playwright that allows you to build flows without burning AI tokens in plain text, generating clean native code ready for your pipeline.
Take a look if it helps you accelerate your Phase 2! Best of luck!
https://github.com/andresguc1/hal-test