vgulerianb

vgulerianb / slapify

Public

Browser automation that finally slaps

11
1
100% credibility
Found Feb 26, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

Slapify lets everyday people automate web browsing, testing, and performance checks by describing tasks in plain English.

How It Works

1
🔍 Discover Slapify

You hear about a friendly tool that automates web browsing and testing just by describing what you want in everyday words.

2
🚀 Set up your space

You prepare your area by running a quick setup that asks simple questions to connect a smart helper and pick your web viewer.

3
Pick your way
🎯
One-time goal

Tell it what to do, like summarize news or check a site's speed.

📝
Repeatable checks

Write simple steps in a file to test logins, shopping, or forms anytime.

4
✨ Watch it go

Hit go and see the helper browse, click, fill forms, and handle surprises like popups all on its own.

5
📊 Get your report

Receive a clear summary with pictures, speeds, and details of what happened.

🎉 Automation magic

Your web tasks now run smoothly whenever you need, saving time and hassle forever.

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AI-Generated Review

What is slapify?

Slapify is a TypeScript CLI for AI-powered browser automation on GitHub, letting you run autonomous agents or E2E tests in plain English. Give it a goal like "summarize top Reddit posts" via `npx slapify task`, or write `.flow` files for tests like "go to checkout, log in, place order" with `slapify run`. It handles logins, CAPTCHAs, popups, and perf audits automatically, outputting HTML reports or structured JSON.

Why is it gaining traction?

Unlike brittle Selenium or Playwright scripts, slapify uses LLMs (Anthropic Claude, OpenAI GPT, Grok) to interpret natural language, skipping selectors and retries. The agent mode self-schedules monitoring tasks (e.g., check BTC price hourly), while flows integrate with Jest/Vitest for CI. As a browser automation tool, it stands out for zero-boilerplate auth and real-user perf metrics like LCP/CLS.

Who should use this?

Frontend devs building E2E tests for login/checkout flows, QA engineers ditching browser automation Python scripts for English, or ops folks automating site monitoring like "alert if status page down." Ideal for Shopify devs scripting Simpsons-episode-style demos or n8n/mcp workflows needing browser steps.

Verdict

Promising early browser automation GitHub project with solid docs and CLI, but only 10 stars and 1.0% credibility signal it's pre-1.0—test on non-critical tasks first. Worth a spin if you hate writing locators.

(187 words)

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