Check a LinkedIn post, ad, email, or landing page for the generic language, missing proof, and weak opening that make marketing feel machine-made. The score measures writing signals—not authorship—and the full eight-part checklist keeps a human responsible for what software cannot judge.
Your text is checked with deterministic rules and is not stored or used for training.
Fix the weakest signal first. Re-score only after the claim, proof, or opening genuinely changes.
Yes. Paste the post above to review its wording, specificity, reader focus, opening, and authenticity signals before publishing. The result cannot prove who or what wrote the post.
LinkedIn product chief Hari Srinivasan says the platform is rolling out improved classifiers, member reporting for content that “seems like AI slop,” and private feedback tests for creators whose posts feel inauthentic or heavily AI-assisted.
LinkedIn’s announcement makes the same distinction as this checker: AI use and low-quality content are not equivalent. Review whether the post contains a real perspective, concrete evidence, and language that belongs to the author—not whether it contains a fashionable punctuation mark.
Use the automated score as an editing prompt, then complete the human review before you publish.
The checker calculates the score with a small, public formula. It measures writing signals—not whether AI was used and not whether a claim is true.
Examples include “revolutionary,” “leverage,” “seamless,” and filler such as “in today’s fast-paced world.”
Applied when copy has at least 12 words but no number, quote, time reference, dollar figure, or other concrete specific.
Applied when copy exceeds 25 words without once addressing “you” or “your.”
Applied when the copy contains at least three concrete signals and directly addresses the reader.
The total is rounded and capped between 0 and 100. Hook and provenance results are reported separately so they do not secretly change the slop score.
Check generic wording, supported claims, differentiation, proof and specifics, opening strength, CTA quality, brand voice, and visual authenticity. Score each criterion 0, 1, or 2. A strong piece earns 13–16. Anything below 9 needs another substantive pass, not synonym swapping.
2: Language belongs to this company and offer. 1: A few replaceable phrases. 0: A competitor could publish it unchanged.
2: Every meaningful claim has evidence or careful qualification. 1: Proof is implied. 0: Superlatives or outcomes appear without support.
2: Names a concrete mechanism, constraint, or tradeoff. 1: Category benefits dominate. 0: No reason to choose this offer.
2: Uses a real number, named example, quote, or dated moment. 1: One broad example. 0: Entirely abstract.
2: Starts on a specific tension or useful open loop. 1: Clear but predictable. 0: Warm-up, throat-clearing, or category filler.
2: One specific, proportionate next step. 1: A generic action. 0: Missing, competing, or disconnected CTA.
2: Matches phrases and convictions the brand actually uses. 1: Competent but neutral. 0: Performs an invented personality.
2: Visual direction shows the real product, process, or evidence. 1: Relevant but generic. 0: Glossy AI imagery substitutes for proof.
Markdown format works in Notion, Google Docs, GitHub, or any notes app.
Replace abstract claims with concrete evidence: a real mechanism, number, example, quote, or dated moment.
“In today’s fast-paced digital landscape, our revolutionary platform leverages cutting-edge AI to seamlessly optimize your marketing workflow.”
Six phrase markers, no mechanism, no proof, and no useful next step.
“Paste your website. MarketMaster researches the buyer, drafts five campaign formats, and blocks publishing until the reviewed version is approved.”
Names the input, mechanism, outputs, constraint, and review boundary without inventing an outcome.
Treat the score as a writing-quality signal, not proof of authorship or factual accuracy.
Generic, interchangeable content marked by hype, vague verbs, unsupported claims, weak differentiation, missing proof, and language that could describe almost any company.
No. This is a writing-quality signal, not an authorship detector. Human copy can be generic, and AI-assisted copy can be specific, accurate, and useful.
Yes. Paste the LinkedIn post into the checker to review generic phrases, specificity, reader focus, opening strength, and authenticity signals. The result is a writing-quality review, not proof that AI did or did not write the post.
No. It can identify whether concrete or provenance-like signals are present, but a person must verify the source and wording of every claim.
No. Reader focus earns relief in this marketing-copy rubric, but narrative, editorial, and brand formats may use a different point of view deliberately.
Use the score as one editing signal, then verify the claim, test a materially different direction, and review the complete package before publishing.
Generate copy from a named audience, benefit, offer, and optional proof instead of a blank prompt.
Score evidence, disclosure, consent, visual plausibility, brand voice, and landing-page fit.
Use a focused preflight for LinkedIn or Reddit when platform norms matter as much as the sentence.
The Ad Studio researches the product and buyer, creates coordinated assets, validates the package, and keeps publishing locked to the exact version a person approved.
Open the Ad Studio