Google Scaled Content Abuse Policy, Explained Plainly

On this page, 7 sections

Google’s scaled content abuse policy targets many pages generated mainly to manipulate search rankings instead of helping users. Google’s wording is that this applies “no matter how it’s created”, so the test is purpose and value, not whether a human or an AI typed the words. Using AI is not the violation. Publishing lots of pages that add nothing is.

I read Google’s spam policies page (last updated 28 August 2026) and its guidance on using generative AI content (last updated 1 October 2026) in full on 11 October 2026. This post sticks to those two pages. Where they are silent, I say “not documented” instead of guessing.

I care because I run a high-volume publishing schedule on this site, and the first thing I checked was whether either page sets a rate limit. Neither does. Here is what they do say, and a short self-audit you can run on your own site.

What the policy actually says

Google defines scaled content abuse as many pages generated for the primary purpose of manipulating rankings and not helping users, typically large amounts of unoriginal content that gives users little to no value. It then lists examples, which it says are not exhaustive. In my words, with the five on Google’s list:

Google’s example (paraphrased)	What it looks like on a WordPress site
Using generative AI or similar tools to generate many pages without adding value	A bulk-published batch of AI drafts nobody checked, researched or tested.
Scraping feeds, search results or other content into many pages, including by synonymizing, translating or other obfuscation, where little value is provided	An import plugin that turns an RSS feed or someone else’s results into posts.
Stitching or combining content from different pages without adding value	A “roundup” built by pasting paragraphs from the top ten results.
Creating multiple sites to hide the scaled nature of the content	The same template network spread across several domains.
Many pages whose content makes little or no sense to a reader but contains search keywords	Keyword-stuffed location or product pages with filler text.

For content you host that falls into these buckets, Google’s remedy is to exclude it from Search. I covered how that mechanism works for crawlers in robots.txt for AI crawlers, though be aware that blocking a crawler and excluding a page from Search are different jobs.

How Google says it finds violations: through automated systems and, as needed, human review that can result in a manual action. Google says sites that violate its policies may rank lower or may not appear in results at all. That is the spam policies page on how it detects policy-violating practices in general, not a statement specific to this one policy.

What neither page says: a publishing rate

I searched the saved text of both pages for rate words: “per day”, “daily”, “per week”, “velocity”, “how many”, “number of pages”, “at what”. I got zero matches in both files. So a posts-per-day threshold is not documented on either page.

That is a limited finding, so I want to label it correctly. It does not prove rate is never an input to Google’s systems; Google does not publish its systems. It shows only that these two pages define the problem by purpose and value, not by how fast you publish.

My inference, labelled as inference: a sudden jump from a quiet site to hundreds of pages is a visible footprint, so every page in a fast run should be able to defend itself on its own merits.

What the generative AI page adds

Google’s gen-AI page makes three practical points.

AI as a research and structure tool is fine. It says generative AI can be useful when researching a topic and to add structure to original content. The warning is about generating many pages without adding value.
Review is required, and it reaches the metadata. Google says generative models predict likely word sequences rather than retrieve facts, so outputs can contain inaccuracies, and it calls manual fact-checking and review before publishing critical. The page says this review also applies to metadata such as title elements, meta descriptions, structured data and image alt text. I wrote about what schema does and does not do in structured data and AI answers.
Give readers context. The page suggests sharing how a piece was created, such as background on how automation was used and image metadata. It frames this as something to consider, not a requirement. A disclosure rule for ordinary blog posts is not documented on the page I read.

The page also points readers to sections 4.6.5 (scaled content abuse) and 4.6.6 (main content with little to no effort, originality or added value) of the Search Quality Rater Guidelines, and says those guidelines are not a guide to ranking first in Google. They are used by raters to help evaluate how its ranking systems perform.

A self-audit that matches the policy wording

You cannot ask Google whether you have crossed the line. You can ask whether each page would survive the policy’s own questions. I use these five on every post before it goes out:

Can I name one thing on this page that does not exist in the top results: a number I measured, a command I ran, a screenshot I took?
Is every factual claim checked against a primary source, including the title and meta description?
Did the page start from a real reader question, or from a keyword list?
If I swap the topic name, does the page still read the same? If yes, it is a template.
Would I be happy with this page being the only one of mine a reader ever sees?

Question four is the one that can be partly automated. The script below compares a list of slugs or titles, one per line, and prints pairs whose similarity is at or above a threshold. A high count of near-identical pairs is the footprint of templated pages. It is a screening tool, not a verdict: two honest posts can share a naming pattern.

#!/usr/bin/env python3
"""usage: near_dupes.py <file-with-one-slug-or-title-per-line> [threshold]"""
import sys
from difflib import SequenceMatcher
from itertools import combinations

def main():
    path = sys.argv[1]
    threshold = float(sys.argv[2]) if len(sys.argv) > 2 else 0.85
    with open(path, encoding="utf-8") as fh:
        items = [line.strip().replace("-", " ") for line in fh if line.strip()]
    hits = []
    for a, b in combinations(items, 2):
        ratio = SequenceMatcher(None, a, b).ratio()
        if ratio >= threshold:
            hits.append((ratio, a, b))
    hits.sort(reverse=True)
    print(f"{len(items)} items, {len(hits)} pairs at or above {threshold}")
    for ratio, a, b in hits[:20]:
        print(f"{ratio:.2f}  {a}  |  {b}")

if __name__ == "__main__":
    main()

I checked it with python3 -m py_compile and ran it on a four-line sample of slugs on 11 October 2026. It printed 4 items, 1 pairs at or above 0.85 and flagged best ai memory layer for agents against best ai memory layers for agents at 0.98.

It compares every pair, so on a list of about 900 slugs it took roughly 30 seconds on my laptop. Export your slugs from WordPress with wp post list --field=post_name if you have WP-CLI.

Questions people ask

Is AI-written content against Google’s rules?

Not by itself, on the two pages I read. The policy’s test is purpose and value, and its wording covers content however it is created. The gen-AI page treats AI as useful for research and structure, and warns about generating many pages without adding value.

How many posts per day is too many?

Not documented. Neither page names a number. What they document is the quality test, so the safer reading is that the number matters less than whether each page earns its place.

Does a human edit make AI content safe?

Google asks for manual fact-checking and review before publishing. A light edit that adds no original value still fits the “without adding value” wording. I would not call any edit a guarantee, because enforcement involves automated systems and human review that the pages do not describe in detail.

Do this today

Export your slugs, run the near-duplicate script, and open the top ten pairs. For each pair, write down the one thing that makes the second page worth a reader’s time. If you cannot, merge it into the first, rewrite it with something you have actually tested, or exclude it from Search. Do that before you publish another batch.

Resources

Google: spam policies for Google Web Search (scaled content abuse section), read 11 October 2026, last updated 2026-08-28 UTC.
Google: guidance on using generative AI content on your website, read 11 October 2026, last updated 2026-10-01 UTC.
Google: Search Quality Rater Guidelines, sections 4.6.5 and 4.6.6, referenced by the gen-AI page. I did not read the PDF itself for this post.
Google: control what you share with Google, the page the spam policy links to for excluding content from Search.

Google Scaled Content Abuse Policy: What It Says and Doesn’t