Paste the draft. Get a 0-100 Authenticity Score in roughly thirty seconds, plus a sentence-level colour map that shows which paragraphs read AI to Google's helpful-content classifier and which read in your own voice. Built for bloggers and content writers checking listicles, how-to guides, reviews, opinion pieces, and evergreen long-form before they ship to WordPress, Ghost, Webflow, or Substack. AdSense-aware framing, keywords preserved across edits, no signup for the first scan.
In 2023 you could publish an unedited ChatGPT draft and rank for a long-tail query inside two weeks. That stopped working in 2024 and is actively penalised in 2026. For bloggers there are three overlapping risks; pre-publish scoring addresses the prose-pattern layer of all three before the post leaves your editor.
Google folded the helpful-content classifier into core ranking in March 2024 and added explicit scaled-content-abuse signals. The 2025 refinements added pattern detection for AI-typical prose. Sites that leaned on unedited drafts have reported losing a meaningful share of organic traffic across subsequent core updates. Scoring before you publish is the cheapest way to catch the prose patterns that contribute to the drop.
The monetization risk is separate from the ranking risk. AdSense is increasingly catching low-value scaled content and disabling ad serving on a per-page or per-site basis. The risk concentrates around thin posts, low-effort niche sites, and YMYL topics. A pre-publish score does not make weak content valuable, but it does prevent the prose pattern from being the thing that triggers a review on otherwise-credible work.
Ranking is not only about the helpful-content classifier. A post that reads generically AI tends to answer the query in a flat, surface way that sends searchers back to the results page within seconds. That pogo-sticking is a behavioural signal search engines can read, and it compounds with the prose-pattern signal. Scoring the draft surfaces the formulaic passages that hollow out the answer, so the post earns the dwell time that holds a ranking instead of bleeding it.
This is the routine content writers use before pushing a post to the CMS. For a 1,500-word piece, plan on 15 to 25 minutes start to finish. The point of sentence-level highlights is that you do not have to rewrite the whole post; you only have to rewrite the parts that read AI.
Drop the full draft into the scoring panel. In about thirty seconds you get a 0-100 Authenticity Score plus a paragraph-by-paragraph breakdown. Save the baseline if the score is below your target so you can measure the delta after rewriting. For posts longer than 800 words on the free tier, paste the intro first, then the body, then the close; the score per section is more diagnostic anyway.
Green sentences passed every signal. Yellow sentences tripped one or two and are usually fine on their own. Red sentences tripped three or more and are the highest-leverage edits. The colour map matters more than the headline number; a score of 65 with three red sentences is easier to fix than a score of 78 spread evenly across yellow.
Work through the red sentences one at a time. The fastest way to lift an AI-flat sentence is to add information a search of the topic would not surface on its own: a screenshot caption, a tool you actually ran, a price you paid, a result you measured, a step that tripped you up. These first-hand specifics are exactly what the helpful-content system rewards and what AI prose strips out. If you use the AI rewriter, stay on Balanced for keyword-driven posts where exact phrasing matters and Light where cadence matters more than ranking.
Paste the revised draft back in. Target 75 for general blog content, 80 for YMYL niches and personal newsletters. Ctrl-F the target keyword phrase to confirm it is still in position. Then copy the cleaned text into WordPress, Ghost, Webflow, or Substack as usual. The free Chrome extension also lets you re-scan inline against the CMS block editor for quick checks during the final edit.
The bands below are calibrated against published blog content across the six formats we tuned the classifier on. Numbers shift slightly by format (review posts run a few points lower than how-to posts at the same prose quality) but the bands below are the working defaults to ship by.
Reads as a real writer working a topic. The helpful-content classifier sees no meaningful AI patterns, so the post competes on the merits of its information rather than fighting a prose penalty. AdSense review risk on prose alone is low. This is the floor for YMYL niches like personal finance, health, and law, where Google and AdSense reviewers spend the most time and where a thin signal does the most damage.
Fine for a weekly links roundup, a guest post, or a quick news reaction where coverage carries more weight than craft. For a money-page or a pillar post you want to rank long-term, push to 80 by editing the red sentences. AdSense risk at this band is low but non-zero and tends to track the rest of the site's pattern rather than the individual post.
Helpful-content classifier risk rises sharply here, particularly on listicles and product reviews where the templated structure stacks with templated prose. A single post is unlikely to sink a healthy domain, but a run of posts in this band feeds the site-wide scaled-content signal. Edit before publishing; this is the band where the rewriting pays the most ranking return per minute spent.
High probability the post pulls down helpful-content signals across the whole site, not just the page. AdSense per-page review odds are meaningful, and for a fresh domain this is the kind of pattern that stalls indexing entirely. Do not publish at this score on a site you want to monetise. Restructure or rewrite; do not paraphrase your way out.
Almost certainly an unmodified ChatGPT or Claude draft. Platform AI tags are near-certain on Substack and Medium. AdSense risk is high on YMYL niches. The fix is to throw out the draft and start from a real observation, not to run it through a paraphraser. Paraphrased prose has its own detection fingerprint that current classifiers flag more aggressively.
ChatGPT defaults to slightly different patterns in each blog format. The scorer adjusts so the bands above match the register the format actually needs, instead of penalising natural genre conventions.
"7 Ways to," "10 Best," "5 Things." ChatGPT writes the skeleton perfectly, which is the problem. The scorer down-weights the parallel sentence opener on every list item and flags it; one or two items written longer than the others, with the parallel opener broken, usually pulls the post out of the risk band.
Numbered steps, prerequisites, screenshots. ChatGPT defaults to a uniform step style with the same imperative opener on every step ("First, open," "Next, click," "Then, save"). The scorer flags monotony in step openers and looks for first-hand friction notes a real practitioner would name. The helpful-content system weights demonstrated expertise on tutorials particularly heavily.
The highest-risk category for AdSense review. ChatGPT defaults to an evenly-positive register that reads sales-y rather than reviewed. The scorer looks for at least one honest negative, a comparison number, or a real-world test result. Reviews without a single concrete dislike read AI to both classifiers and to attentive readers.
Personal stance, argument, takeaway. ChatGPT hedges every claim and softens every position into a generic centrist register. The scorer rewards sharpened claim sentences and personal stake (a specific example, a number, a contrarian observation). Opinion pieces that read like everyone-could-have-written-this read AI.
The 2,000 to 4,000 word pieces that anchor most content sites. ChatGPT structures these with template H2s and bullet-heavy bodies; the cumulative effect across sections is what trips the classifier. Score section by section instead of as one chunk so the band tells you which part of the post needs work, not just that something does.
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E-E-A-T is the lens Google's reviewers use to judge whether a page deserves to rank in 2026. The scorer cannot fabricate real experience for you; what it can do is keep the prose patterns from being the thing that flags an otherwise-credible post.
"Experience" was added in late 2022 specifically because expertise alone was being gamed by AI-assisted content. It means demonstrated first-hand encounter with the topic: a tool you actually used, a place you actually visited, a result you actually measured. ChatGPT cannot generate this; it can only mimic the surface. The scorer flags sections where the prose sounds experienced but the content is generic, so you can drop in the real anchor before publishing.
Expertise is signalled by terminology, specificity, and willingness to take a position. ChatGPT's default register is the opposite: hedged, generic, evenly-balanced. The scorer flags claim sentences that read like a research summary and rewards posts that commit to a specific position rather than surveying three options.
Trust signals are the small honesty cues: a caveat that contradicts the headline, a disclosure of limitations, a "we tried this and it did not work" paragraph. ChatGPT removes these by default because they hurt the surface-level confidence of the prose. The scorer rewards their presence and flags posts that read suspiciously frictionless.
If your blog post scored low, here is the editorial AI rewriter tuned for listicles, how-tos, reviews, and evergreen long-form.
Open AI rewriter →The full bloggers' workflow page covering Google helpful-content context, AdSense compliance, and the publish-day routine.
Open the detector →The sister page for SEO and content-marketing articles, with the same scoring engine and bands tuned for ranking-focused content.
Score an article →How the 0-100 score is computed, which signals carry the most weight, and what threshold to aim for before you publish.
Read the guide →Free to try, no card. 0-100 score in thirty seconds, sentence-level highlights, AdSense-aware, keywords preserved.
Run the Authenticity Score on the exact thing you're about to send.