Dev.to WebDev 🛠 Dev 👁 0 📖 1 min read

I built a free pore-clogging ingredient checker that runs 100% in your browser

If you have acne-prone skin, you have probably Googled "is [ingredient] comedogenic" more times than you can count. I kept doing that too, so I built a small tool that does it in bulk: Pore Clogging Checker - https://por

If you have acne-prone skin, you have probably Googled "is [ingredient] comedogenic" more times than you can count. I kept doing that too, so I built a small tool that does it in bulk: Pore Clogging Checker - https://porecloggingchecker.app

What it does

Paste a product's full ingredient list (or upload a photo of the label and let OCR handle it), and the tool flags every ingredient on a 0-5 comedogenic scale. Ratings trace back to published dermatology literature - Fulton's 1989 comedogenicity study and related work - and every flag shows its source, so you can judge the evidence yourself instead of trusting a marketing "non-comedogenic" label.

How it's built

The interesting constraint was privacy: ingredient analysis runs entirely client-side, in the browser. Nothing you paste leaves your machine. The matching layer does exact, alias, and localized-name lookups across 9 languages, with a Levenshtein fallback for OCR noise - because ingredient lists on packaging are rarely typo-free. The whole app deploys as a Cloudflare Worker; there is no traditional server holding your data.

Why fungal acne is a different beast

One thing we learned building this: "acne" isn't one problem. Fungal acne (malassezia folliculitis) reacts to a different set of ingredients - esters and fatty acids with certain chain lengths feed it, while classic pore-cloggers may be fine. Our dedicated fungal acne checker handles that separate rule-set, and there is a Korean-language version here: https://porecloggingchecker.app/ko/tools/fungal-acne-checker

Try it

No signup, no paywall: https://porecloggingchecker.app - paste an ingredient list and see the flags. If you build skincare-adjacent tools too, I'd love to hear how you handle ingredient data quality; it's a messier dataset than it looks.

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