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Filters trademark-squat pseudo-brands out of Amazon search results. Runs entirely offline — no accounts, no tracking, no network. Search Amazon for anything and you'll meet the same wall: forty listings from brands you've never heard of, with names that look like a cat walked across a keyboard. SZHLUX. HORUSDY. AOOKUU. They're trademark squats registered in bulk so a seller can list on Amazon, and they bury the products you actually wanted. Brand Filter reads the brand on every listing and marks the ones with nothing behind them. How it decides Every listing is checked against a bundled list of 4,000+ real brands, a list of known pseudo-brands, and a language model that scores how a name is built — all-caps, missing vowels, impossible letter runs, digits wedged into the middle. The language model covers eleven languages, so real brands aren't mistaken for junk. Kärcher, Schwalbe and Zojirushi read as ordinary words, because they are. It includes a romanised Indic model as well, which matters on amazon.in — Sujata, Kanchan and Kamdhenu are perfectly regular names that an English-only filter reads as gibberish. You stay in control Three strictness levels. Filtered listings can be dimmed, hidden, or just labelled — start with dimming and watch what it does before you trust it. Type any brand into the settings page to see exactly what the filter makes of it and which signals fired. Disagree? Add it to your trust list in a click, or paste a whole list at once. Your lists override everything, including the built-in ones. You can also filter by minimum star rating and review count, and hide listings with no ratings at all. What it doesn't do No network requests — not on install, not on a schedule, not when you open a listing. The brand lists and language model ship inside the extension. Nothing about your browsing is collected, stored remotely, or sent anywhere. Works on 23 Amazon marketplaces. Brand data includes the AmazonBrandFilterList by Chris Mosley, used under the MIT licence.
Aug 14, 2026
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.