A spelling error in the H1 heading, a typo in the product price, a case mismatch in the description. AI can overlook minor typos if they don't distort the meaning. But gross spelling errors, factual contradictions, or typos in numbers will be noticed by the model, reducing trust. This isn't a "schoolteacher" that deducts points for every comma. It's an algorithm looking for quality signals. Errors are noise. The more noise, the lower the trust and the chances of being cited.

In this article — which errors AI forgives, which it doesn't, how to calculate the "acceptable level," and what to do if errors already exist.

Errors AI Almost Always Catches

Some errors are critical for the model. They distort meaning, contradict facts, or reveal unprofessionalism. Here they are.

Numbers and facts. Example: one page says "experience since 2015," another says "since 2018." The model sees the discrepancy and doesn't know which figure to trust. The price in the product card and in the cart differ. The model may flag the inconsistency and lower trust. The article's publication date and the date in microdata don't match. The model may consider the data unreliable.

Contradictions within the same text. Example: "The laptop weighs 1.5 kg" and a paragraph later "weight 2 kg." "Warranty 12 months" and "warranty 1 year" — the model can't determine which statement is correct.

Gross spelling errors in key elements. Example: "Kupit notebook" instead of "Buy notebook" — the model may not understand the page's intent. "Seo-prodvizhenie" instead of "SEO-prodvizhenie" — reduces trust in professionalism. "Promo: -50%" without specifying the original price — the model can't verify it.

Errors in proper names and brands. Example: "Apple" written as "Aple," "Yandex" as "Yandex." The model may not understand which brand is meant and won't use the page. A professional website audit for search engines helps identify such errors.

Errors AI May Forgive

The model isn't perfect. Minor errors that don't affect meaning may slip through. But "may" doesn't mean "definitely will." The risk remains. The fewer, the better.

A typo in one character in the middle of a long word. Example: "krasivyy dizayn" instead of "krasivyy dizayn." The model may guess from context. But if there are many such typos, the model starts doubting.

A missing comma in a long sentence. The model doesn't evaluate punctuation like a schoolteacher. A comma doesn't affect meaning. But if its absence makes the sentence ambiguous — that's a problem.

Case mismatches in a long phrase. The model understands meaning even if grammar is shaky. But systematic errors reduce trust. "Ikhniy" instead of "ikh" — the model will understand but perceive it as illiteracy.

English words inserted into Russian text without transliteration. Example: "We offer best solution for your business." The model may understand "best solution." But it's better to write in one language. Mixing languages adds extra noise.

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How Errors Affect Trust: A Gradation

The model doesn't count errors in points. It assesses the overall impression of the page. The more errors, the lower the trust. Here's an approximate gradation.

0–1 errors per 1000 characters (excellent). The model perceives the page as high-quality and professional. The chance of being cited is high.

2–3 errors per 1000 characters (average). The model may not notice if errors are minor. But the risk is already there. The chance of being cited is average.

4–6 errors per 1000 characters (poor). The model starts doubting quality. The chance of being cited is low. The page may be ignored even if the content is good.

More than 6 errors per 1000 characters (critical). The model perceives the page as low-quality and unprofessional. The chance of being cited is near zero.

Important: errors in numbers, contradictions, and spelling in key elements (headings, prices, dates) carry more weight than errors in long descriptions. One error in a price outweighs 10 typos in the text. High-quality content creation helps avoid most problems.

How to Find and Fix Errors on Your Website

Method 1: Use spelling check services. Text.ru, Advego, Orfogrammka. They'll find typos and grammar errors. Upload the page text or check by URL. But these services don't check numbers, dates, or prices — that needs to be done manually.

Method 2: Manually proofread key pages. Homepage, service pages, product cards, "About Us," "Contacts." Errors here are most critical. Read slowly, aloud. This makes it easier to spot inconsistencies and missing words. Ask a second person to read — a fresh eye catches more errors.

Method 3: Use AI for checking. Copy the page text into ChatGPT, DeepSeek, GigaChat. Ask: "Find spelling, grammar, and factual errors in the text. Point out contradictions in numbers and dates." AI is good at finding logical inconsistencies. But verify manually — the model can be wrong on facts, especially if the error is in a number the model doesn't know.

Method 4: Validate microdata with validators. Errors in structured data (wrong types, empty fields, mismatch with visible content) can be noticed by the model. Google's or Yandex's validator will show errors. Fix them by priority.

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Text Quality for GEO vs. for People

AI doesn't grade style. It doesn't care if you write in bureaucratic or conversational language. Commas, dashes, quotes — the model doesn't evaluate them. But errors that change meaning will be noticed. Factual contradictions, incorrect numbers, inconsistent data — the model will filter them out. Spelling in key places affects trust in professionalism.

What matters to people but not to AI. Style: bureaucratic vs. conversational — the model doesn't care. Vocabulary richness: simple words are fine. Sentence length: what matters is avoiding long paragraphs, not long sentences. Emotional coloring: the model ignores it.

What matters to AI but people may not notice. Consistency of numbers across pages (price in the card and in the cart). Consistency of NAP data (address in the footer and on the "Contacts" page). No factual contradictions. Microdata. People may not notice that the address in the footer is written differently than on the "Contacts" page. The model will.

Practical Recommendations

Priority 1: Check numbers, dates, and prices. The price in the product card, in the cart, and in microdata must match. Publication and update dates, company founding dates — must be consistent. Work experience, project counts, percentages — must be realistic and non-contradictory.

Priority 2: Eliminate factual contradictions. Warranty: one page says 12 months, another says 1 year. Product specs: table shows one set of numbers, description shows another. Delivery terms: one section says free from 3000 ₽, another says from 5000 ₽.

Priority 3: Check spelling in key elements. H1 (main heading), H2 (subheadings), product and service names, meta descriptions. Errors here are most noticeable.

Priority 4: Check spelling in the rest of the text. Use spelling check services. Read the text aloud. Ask colleagues to review. Remember: the more errors, the lower the trust.

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Conclusion

AI doesn't forgive systematic errors. It may overlook one or two typos per page, but each additional one reduces trust. Critical errors (numbers, contradictions, spelling in headings) are almost always noticed.

The acceptable level is 1–2 errors per 1000 characters, and not in key elements. The ideal level is 0 errors. Errors don't "kill" a page instantly, but they reduce the chances of being cited. In a competitive niche, even one error can be the reason the model chooses a competitor over you.

Check your key pages. Find and fix errors by priority: first numbers and contradictions, then spelling. Remember: the model isn't a schoolteacher. It doesn't deduct points for every comma. But it assesses overall quality. The more errors, the lower the trust. The lower the trust, the fewer chances AI will cite your site.

Frequently Asked Questions

Should I remove all commas to make it easier for the model to read?
No. Commas don't bother the model. It ignores them. Removing commas can make the text harder for people to read. Don't worsen the text for people for imaginary AI benefits. Commas aren't an error.

How to check if an error in a number is not critical?
Ask yourself: could this error affect a user's decision? If a user sees the cart price higher than the card price, they'll leave. That's critical. If a user sees work experience as "5 years" instead of "6 years" — they might not notice. But the model might. Better to fix all inaccuracies.

What to do if there are many errors but no resources to fix them?
Prioritize pages that aim to be cited (homepage, services, products). Fix errors there first. Leave other pages for later. Even partial fixes are better than nothing. Errors on pages nobody reads and that aren't cited aren't scary. Errors on important pages are critical.

Do grammar errors affect rankings in classic SEO?
Indirectly, yes. A user sees an error and leaves the site. Behavioral factors worsen. Rankings may drop. But search engine algorithms don't directly penalize grammar. For AI models, grammar matters more than for classic algorithms because models assess source quality.