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Abhishek Saikia

KushoAI for Playwright - Open-source Terminal UI, just record & get exhaustive tests

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KushoAI
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Open-source TUI for Playwright testing. Record your flow in the browser, then everything happens in your terminal. No tab-switching to ChatGPT/Claude, no copy-pasting, no manual context juggling. Bring your own API key (OpenAI, Claude, Gemini). Runs entirely local. Our LLM orchestration expands one recording into comprehensive test coverage - edge cases, error handling, boundary conditions - more efficiently than calling LLMs directly. Record, generate, run: all terminal-native. MIT licensed.

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Abhishek Saikia
Maker
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Hey Product Hunt! 👋

I'm Abhishek, CEO at KushoAI. I'll be honest about why we built this.

Playwright is great. The problem isn't the tool. The problem is that writing comprehensive tests by hand takes forever. You write a test, a selector breaks, you rewrite it, the flow changes, you do it again. You end up shipping with partial coverage because you're out of time.


Here's what we built:

Record your user flow once using Playwright's browser recorder. Close the browser, and the generated script opens in your terminal editor. Review it, tweak it, save it.

Then our TUI orchestrates LLM calls to expand that single recording into comprehensive test coverage: different input combinations, boundary conditions, error states, edge cases. You can guide it with plain-English instructions ("add error handling tests", "test with special characters").

The whole workflow stays in your terminal. No tab-switching to ChatGPT, no copy-pasting context, no manual prompt engineering. Record in browser, generate in terminal, run tests, get HTML reports.


Key details:

  • Fully open-source (MIT licensed)

  • Runs entirely local, your API keys stay on your machine

  • Supports OpenAI, Claude, and Gemini (bring your own key)

  • Interactive TUI menu if you prefer guided workflows over typing commands

Why we're building this:

KushoAI started with API testing. Developers kept asking about UI testing. Both problems share the same root cause: writing exhaustive tests manually doesn't scale. We're betting that AI-native testing infrastructure is how modern teams actually achieve real coverage.

I'd genuinely love feedback on:

  1. Is the current setup too complex? (Considering making it a single npm install command)

  2. What frameworks beyond Playwright? (Python/pytest is the most requested)

  3. What's the first flow you'd want to test on your app?

Star the repo if this is useful, and drop your toughest UI testing problem in the comments. I'm here all day.

GitHub: https://github.com/kusho-co/kusho-ui-testing-tui
Docs: https://resources.kusho.ai/kusho-ai-ui-testing-tui

Saul Fleischman

@abhishek_saikia This is a solid workflow improvement—the friction of maintaining selectors and test coverage is real. The terminal-first approach makes sense for developers who already live there, and keeping API keys local is a good call. Curious how it handles cases where the LLM-generated assertions miss actual bugs that a human would catch, or if you've seen patterns in what kinds of coverage gaps still slip through.

Abhishek Saikia
Maker

@osakasaul Great question. The workflow is designed for this: after recording, the Playwright script opens in your terminal editor before any AI generation. You review the base test, adjust selectors, add critical assertions, then save. Human judgment first, then AI expands the coverage.

What slips through: Complex business logic assertions (pricing rules, state-dependent behavior), visual regression checks. The LLM doesn't know your domain.

What it handles well: The 70% of tests teams skip like boundary conditions, special characters, error message validation, empty states.

We're solving for breadth (edge cases you'd write if you had time), not replacing depth (knowing what actually matters). What's your current approach for coverage gaps?