JsPad is a web-based HTML/CSS/JS editor focused on speed, simplicity, and offline access. No bloat — just open and start coding.

What makes it different:

Live Preview – Edit HTML, CSS, and JS side-by-side with instant feedback.

Offline support – Works without internet. You can even install it as a PWA and use it like a native app.

Cross device support– It is responsive across different resolutions. PWA availability on iOS and android makes it even better. Use it on windows, macOs, iOS, Linux or android.

No Login Required – Just visit, code, and preview. Login only if you want to save/share.

Savable & Shareable Links – Save scripts in the cloud and get shareable links.

Customizable Editor – Themes, fonts, auto-format on save, layout tweaks, line wrapping, etc.

Hotkey Support – Power user shortcuts with tooltips showing keybinds.

Export your code to zip or Github gist – Export your project with HTML/CSS/JS files separated.

Ideal for tinkering, prototyping, teaching, or even building micro-tools. It’s intentionally simple, fast and accessible.

How do I upload assets programmatically? Through CI/CD flow essentially.

Record and share your code snippets, algorithms with ASMR ambience.

‎ https://whatsapp.com/channel/0029VaFXAGoIyPtaX196ef3T

Search for npm packages, within VSCode. View the readme and other details of any npm package, within VSCode. View installed and latest available version of installed dependencies, with colored labels indicating how outdated your dependencies are. Install, upgrade or uninstall any npm package. View all dependecies and their dependecy trees. Add or execute scripts from package.json, without touching terminal or package.json.

How exactly does it validate the idea behind the scenes? What data point it seeks from me as input to be able to correlate it with reliable indicators in the backend?

Thanks for the questions and they're good ones too :)

Our idea validation (idea checker) feature analyzes intuitive (hunch) ideas to check their idea uniqueness and business viability against our collections of companies and products, both active and inactive, in our database.

Both components have their sets of questions (datapoints) which we ask, such as:

- for idea uniqueness: one-sentence pitch, industry, business model type, market, and so on

- for business viability: what problem is being solved, what is the solution, who are the customers, how big is the market, and so on

So we'll analyze our users' inputs to predict their failure rate based on their idea uniqueness, competitive landscape, novelty score and so on.

Feel free to check out our solutions as we offer Freemium Plan for users to try us out: https://www.flipidea.co/

*Note: due to our real-time analysis (using text analytics), our results waiting time may take up to 1 min, which we're working to reduce the waiting time, and we're also improving its accuracy by our major release next month.

You probably want fuzzy search: https://en.m.wikipedia.org/wiki/Approximate_string_matching