Find the AI slop in your LinkedIn post. Then fix it.

Why LinkedIn is cracking down on AI slop

In May 2026 LinkedIn said that when content “appears to be generated by AI and lacks clear perspective,” it is less likely to be widely distributed beyond a person's immediate network. In July 2026 it added a “Seems like AI slop” option so members can report posts that read machine-made, plus new classifiers that cut slop from recommendations outside your network. Authors now get a private alert in their dashboard when readers feel a post comes off as inauthentic. LinkedIn's line on AI help is simple: it is allowed, but your content “should still reflect the member's own voice, perspective, and experience.”

What this AI slop detector flags

General AI detectors look for patterns in any text. LinkedIn slop has its own dialect, so this detector carries a list of 50 LinkedIn-specific tells, grouped into eight checks that add up to a 0 to 100 score:

• Engagement-bait closers, 15 points. “Agree?”, “Comment YES”, “Tag someone who needs to hear this”. LinkedIn itself asks members to avoid direct asks for engagement and tagging for attention.

• Contrast turns, 15 points. “It's not about X. It's about Y.”

• Stock framing, 15 points. “In today's fast-paced world”, “Here's what nobody tells you”, “Let's dive in”.

• Format tells, 15 points. One sentence per line for the whole post, emoji bullets, arrow sub-bullets, stacked em dashes.

• Announcement openers, 10 points. “Thrilled to announce”, “Humbled and honoured”.

• Story shells, 10 points. “Let that sink in”, the stranger who said something you will never forget, the wedding that taught you about B2B sales.

• Stock words, 10 points. Delve, tapestry, leverage, seamless, game-changer.

• Generic gratitude, 10 points. “Grateful for this amazing community”, with nobody named.

Every flag shows the exact phrase and a human swap: what a person would actually say instead.

Why there is no “AI probability” here

Probability detectors guess, and they guess wrong often enough to accuse real people. A tell is not proof either: plenty of humans write “Thrilled to announce”. So this tool shows its evidence and never claims to know who wrote a post. The question it answers is narrower and more useful: which lines will make a reader, or LinkedIn's classifiers, file your post under slop? For text that is not a LinkedIn post, use our general AI detector. To rewrite a flagged passage, try humanize AI text.

How to fix a flagged post

• Swap, then add. Removing tells makes a post clean, not good. Add one detail only you know: a number from your work, a name, what it cost.

• Pick a side. LinkedIn says its systems are trained to recognize content that adds perspective, context or expertise. A post anyone in your industry could sign has none.

• End on your best line. Not on a question you do not want answered.

• Keep your own habits. If you have posted in short lines for years, that is your voice, not slop. The format check only fires when a whole long post is one line per sentence.

Need a better first line once the stock opener is gone? The LinkedIn hook generator gives you options.

The real fix is starting in your own voice

Scrubbing tells out of an AI draft is slow, and the result still sounds like nobody in particular. VoiceMoat starts from the other end. audenAI, the brain inside VoiceMoat, learns from your own LinkedIn content, then drafts posts and comments in your voice and checks drafts so they sound like you. The Chrome extension drafts comments right inside LinkedIn, so even your replies carry your perspective instead of the “Great insights!” register readers now skip.