Content Effort Grader
Google’s leaked ranking documentation includes contentEffort, an LLM’s estimate of how much human work went into an article. Grade any blog post or draft on the evidence that model can see, and learn what would make your page expensive to copy.
From the AI Search Optimization toolset.
How we reverse-engineered contentEffort
In May 2024, internal documentation for Google’s Content Warehouse API became public. Inside the page-quality module QualityNsrPQData sits an attribute called contentEffort, described as an “LLM-based effort estimation for article pages.” Google has never published how that model is prompted or trained. It has published the definition its human quality raters work from, and the questions it asks publishers to put to their own content.
The rater guidelines define effort as “the extent to which a human being actively worked to create satisfying content,” alongside originality and talent or skill. They reserve the Lowest rating for main content that is copied, paraphrased, AI-generated or reposted “with little to no effort, little to no originality, and little to no added value.” A language model estimating effort has only the page to go on, so the grader scores the evidence on the page: everything a careful reader would point to as proof that someone did the work.
Underneath all of it sits one practical test, replication cost. If a competitor or a model could rebuild your page from the top ten results in an afternoon, it carries little effort however long it runs. Each pillar below measures a different part of what would be hard to copy.
| Pillar | Points | What the grader measures | Where it comes from |
|---|---|---|---|
| Original assets | 22 | Original images versus stock, screenshots, charts and diagrams, video, interactive and data embeds, data tables, numbered procedures. | Rater guidelines: effort, originality, and talent or skill. |
| First-hand experience | 26 | First-person statements of use and testing, original data or research, a described methodology. | Self-assessment: "original information, reporting, research, or analysis" and "first-hand expertise". |
| Depth & expertise | 22 | Main-content substance, density of specifics (figures, named products, people and places), trade-offs and caveats. | Self-assessment: "insightful analysis or interesting information that is beyond the obvious". |
| Commodity signals | 18 | Stock and AI-boilerplate phrasing, uniform sentence rhythm, repeated five-word phrases, template section headings. | Rater guidelines: the Lowest rating for content made with little to no effort, and scaled content abuse. |
| Who & how | 12 | A named author with a bio link, cited primary sources, attributed quotes. | The Who, How and Why questions: "clear sourcing, evidence of the expertise involved". |
Reading the grade
- Main content only. Navigation, related-post rails, newsletter boxes and footers are stripped before a word is counted, so template text never inflates a score.
- Evidence is what counts. A model can only credit the work a page shows. A genuinely tested review that never says how it was tested reads like a summary, so the grader rewards pages that show their work.
- One signal among many. contentEffort is one input among hundreds and its weights are private. The score is most useful for comparing your own pages with each other, and with competitors, on the same scale.
- JavaScript-rendered articles. If a page builds its article in the browser, the fetch can come back thin. Paste the text as a draft to grade it.
- Free and private. The page is fetched, graded and discarded. Nothing you grade is stored.
Content effort FAQ
What is contentEffort in Google’s ranking systems?
contentEffort is an attribute in the QualityNsrPQData page-quality module of Google’s Content Warehouse API documentation, published in May 2024, where it is described as an “LLM-based effort estimation for article pages.” Most analysts connect it to the helpful content system, which Google folded into its core ranking systems in March 2024.
Has Google confirmed how contentEffort is used?
Google has not explained how individual attributes in the documentation are weighted or applied. What Google does publish is guidance that rewards original, first-hand, people-first content, and a rater definition of effort. This grader is built on that public guidance, so every point it awards traces back to something Google has said in writing.
Does word count affect content effort?
Only indirectly. Google says it has no preferred word count, and this grader gives length 6 of 100 points. Longer pages simply have more room for the signals that carry the weight: first-hand detail, original data, trade-offs and custom visuals.
Can AI-assisted content score high?
Yes, when the effort shows. Google’s guidance targets content made with little effort or originality, whatever produced it. A draft built on your own testing, data, screenshots and named expertise scores well even if a model helped with the prose. Unedited output with stock phrasing and no first-hand evidence scores low.
How do I raise a low score?
Start with the three upgrades the grader lists, ranked by the points each recovers. The fastest gains usually come from a short methodology section, annotated screenshots or charts of your own data in place of stock images, and a plain account of what you personally tested or observed.
Sources
- Google Search Central, “Creating helpful, reliable, people-first content”
- Google, “Search Quality Rater Guidelines”
- Google Search Central Blog, “What web creators should know about our March 2024 core update and new spam policies”
- Hobo Web, “What is Google’s content effort signal?”
- Cyrus Shepard, “Content Effort: The Google Ranking Feature Nobody Talks About”
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