An AI LinkedIn rewriter built around the fold

LinkedIn's format rewards a specific structure: a hook strong enough to earn a tap past the truncation point, short paragraphs, and a voice a reader can attribute to one person rather than a template. This tool takes an AI-drafted post, or one that reads as one, and rewrites it into that structure without altering what it argues.

The rewrite is server-side, text is sent to our AI server, processed and returned, since producing a genuinely distinctive sentence is work a language model performs. The allowance is 5 free runs per rolling 24-hour window, no account required.

A minute spent scrolling the feed surfaces the same sequence of moves across unrelated authors. The sameness itself is the signal, more reliably than any individual word choice.

The unearned hook

An opening line that fails to justify the tap past 'see more', or that surrenders the point before the truncation even occurs.

One sentence per line

Every paragraph reduced to a single sentence, legible as a formatting reflex once applied uniformly across an entire feed.

The appended question

'Agree?' or 'What would you do?' attached regardless of whether the post substantively invites a response.

The broadcast register

Confident, upbeat and faintly corporate, indistinguishable across accounts with unrelated subject matter and unrelated authors.

The process is intentionally brief: three steps, no configuration.

Step 1

Paste the draft, including the hook where one already exists.

Step 2

Run it. The text is sent to our AI server, rewritten, and returned within a few seconds.

Step 3

Confirm the hook earns the tap, then copy the result. The interface shows how many of your 5 runs remain.

LinkedIn truncates a post after roughly two or three lines behind a 'see more' link. A hook that fails to earn that tap means the remainder of the post, whatever its quality, is never read. That single line accounts for more of a post's performance than everything beneath it combined.

A post that reads as templated also forfeits what LinkedIn's format actually rewards: recognition of a specific author's perspective. Generic phrasing is scrolled past for exactly that reason, regardless of the substance underneath it.

A model trained on a large corpus of posts learns the structure that performs best on average and applies it independent of who is actually writing, which is why an AI-drafted post from a marketer and one from an engineer can read almost identically in hook shape, paragraph length and closing device.

It rewrites the hook, restructures the text into the shorter paragraphs the format rewards, and varies sentence rhythm so the post departs from a recognizable formatting template. It flags an appended engagement question where the remainder of the post does not substantively earn one.

It does not invent an opinion, a result or a story absent from the source. The author's argument, figures and experience are preserved exactly as submitted. Reviewing the output before publishing remains the author's responsibility, and takes only a moment.

No, and no honest tool can. Engagement depends on timing, the author's existing network and the platform's distribution behavior on a given day, none of which a rewrite controls.

What it reliably corrects is a post's tendency to read indistinguishably from every other post in the feed. That is a genuine improvement in whether the post is read at all, and it is stated as exactly that, not as a promised outcome in likes or comments.

Professionals building a public presence who used a model to produce a post quickly but do not want their output reading identically to every other account in their field. Founders, recruiters and consultants publishing often enough that a templated voice becomes visible over time.

It is equally useful for the single post that carries real weight: an announcement, a career update, a draft revised several times without landing. Paste it, run it once, and confirm the hook earns the read it needs.