5 items
Analyzes LinkedIn private messages to verify their human authenticity based on LinkedIn community reports. Tired of getting those automated LinkedIn messages from "salespeople"? Mark those "spammers" easily so they don't spread all over the network. It's very easy to use. If you think the message you receive is spam, just report it. If several people have reported it, it will appear as reported, so you will know that this message has been sent to hundreds of people. The icons are only available on those people who wrote to you first, and only on their first messages. Claim a clean network, where, if they want to sell you something, they don't treat you like a flyer in a mailbox. It works even with similar messages, even if you change the name, or the company name, or some phrase (which is what mass mailing bots allow you to do), Wham detects similar messages when someone reports them.
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.