5 items
Flags long LinkedIn posts that read like generic, low-value writing. Scoring stays on this device. FluffSift flags long LinkedIn posts that rely on stock phrases, repeated wording and familiar writing formulas. Each flag explains the patterns it found, so you can decide whether to keep reading. Choose how flagged posts appear By default, FluffSift adds a small “Generic-style” badge and leaves the post visible. For posts marked “High,” you can choose to dim the text or collapse the post. “Medium” matches remain visible with a badge. You can also: - Open a flag to see why the post was marked. - Adjust how readily FluffSift flags posts. - Remove a flag using “Looks human.” - Hide an individual post using “Hide this one.” - Turn FluffSift off to restore your feed. Your settings and choices for individual posts are remembered on your device. Posts are checked locally FluffSift processes post text in your browser. It does not upload post text or browsing activity, and you do not need a FluffSift account. What to expect FluffSift checks writing patterns. It cannot determine whether AI wrote a post or whether the information is correct. Useful posts can share these patterns too, which is why you can review the reasons and override a flag. The current version checks English-language posts on LinkedIn feed and individual post pages in Chrome on desktop. Not affiliated with LinkedIn.
Nov 7, 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.