ℹ️ Geodeck is built by the team behind Seofable, an AI-era SEO content tool. Seofable is listed in our directory as a clearly labeled featured listing; rankings and recommendations in this article are editorial.
What Is a GEO Score Checker?
A GEO score checker is a tool that audits a single URL against a set of content and technical rules, then outputs a number, usually 0 to 100, meant to estimate how "ready" that page is to get cited by an AI answer engine. GEO stands for Generative Engine Optimization, a term that started circulating around 2023 as marketers noticed ChatGPT, Perplexity, and eventually Google AI Overviews were pulling answers from specific pages and sometimes naming sources, sometimes not.
The scoring idea borrows directly from decades of SEO tooling. Yoast built a green light for keyword density and readability. Ahrefs built a Domain Rating. GEO checkers do the same thing for a newer problem: instead of "will Google rank this," the question is "will an LLM quote or cite this."
I ran the same product page through three different checkers last month for a client audit. One flagged it at 38 for "missing direct-answer format." Another gave it 71 and praised the FAQ schema. Same URL, same day, wildly different verdicts. That gap is the whole reason this comparison exists.
GEO vs traditional SEO scoring
Traditional SEO scores measure rankability signals: keyword placement, backlinks, page speed, meta tags. GEO scores measure extractability and citation-worthiness instead, things like whether a paragraph answers a question in one self-contained sentence, whether stats have a named source, and whether schema markup gives an LLM a clean data structure to lift from. A page can rank #1 on Google and still get ignored by ChatGPT's answer synthesis if it buries its answer in paragraph four behind a 200-word intro.
Why AI engines need a different scoring model
AI engines don't rank ten blue links, they generate one answer and decide which sources, if any, to surface or cite. Google's own AI Overviews documentation describes the system using a "query fan-out" technique that issues multiple related searches across subtopics and identifies a wider, more diverse set of supporting pages rather than linking to a single "best" page the way classic search does. Both AI Overviews and AI Mode may use a "query fan-out" technique, issuing multiple related searches across subtopics and data sources, to develop a response, and while responses are being generated, advanced models identify more supporting web pages, allowing display of a wider and more diverse set of helpful links than with classic web search, which is why optimizing for "position one" doesn't automatically translate into being the source an LLM pulls from (Google Search Central).
What GEO Score Checkers Actually Measure
Most checkers score a fixed list of heuristics pulled from the page's HTML and text, not from an actual conversation with an LLM. The five recurring categories, across the tools we tested, are structure, schema, authority signals, freshness, and llms.txt presence.
Structural & answer-format signals
This is usually the heaviest-weighted bucket. Checkers look for a direct answer within the first 1-2 sentences of a section, question-phrased H2s and H3s, short paragraphs (commonly under 4 sentences), and the presence of lists or tables that break information into extractable chunks. A page that opens every section with three sentences of context before the answer will get marked down here, regardless of how good the content actually is.
Schema and structured data
Structured data gives an LLM a machine-readable shortcut instead of forcing it to parse prose. Checkers scan for FAQ schema, Article schema, Organization schema, and increasingly for an `llms.txt` file, a proposed convention (not yet a web standard) that tells AI crawlers what content on a domain is meant for their consumption. Google's Search team has publicly and repeatedly stated that llms.txt isn't needed for visibility in its generative AI features Google Search says llms.txt isn't needed for visibility in generative AI Search features, so its actual impact on citations remains unproven, but most GEO checkers score its presence anyway as a forward-looking signal.
Authority and citation signals
E-E-A-T (Experience, Expertise, Authoritativeness, Trust) shows up here in GEO form: named authors with bylines, dated statistics with a linked source, external citations to primary data, and outbound links to recognizable domains. Content freshness also lands in this bucket, since several checkers penalize pages without a visible "last updated" date or with a publish date older than 12-18 months.
Free GEO Score Checkers Compared
We ran the same test URL, a 1,400-word how-to article with FAQ schema and one author bio, through eight tools that market themselves as GEO or AI-visibility score checkers. Here's what each one actually does, based on their published methodology pages and our own scans, not their marketing copy.
| Tool | Engines referenced in scoring | Free tier | Methodology disclosed? | Output format |
|---|---|---|---|---|
| Frase | Generic LLM heuristics, not engine-specific | 1 doc/scan on trial, then paid | Partial (scoring rubric summarized) | Score + content brief suggestions |
| Topify | ChatGPT, Perplexity referenced | 1 free URL scan | Minimal, marketing-language only | Score + upsell to full audit |
| geo-score.online | Not specified per engine | Free unlimited basic scan | None published | Score + generic checklist |
| geoscorechecker.com | ChatGPT, Gemini mentioned | Free, email required for full report | None published | Score + PDF report |
| Context.dev | ChatGPT, Perplexity, Claude | Limited free scans | Partial, blog explains factors | Score + structured recommendations |
| Glippy | Generic "AI engines" | Free single scan | None published | Score only, minimal detail |
| Geoptie | Not specified | Free scan, paid for history tracking | None published | Score + basic breakdown |
| Readdy | Generic content audit, not engine-specific | Free scan | None published | Score + fix suggestions |
Two things jump out. First, most tools describe "AI engines" in the abstract rather than naming which one their heuristics actually target, which matters because a page optimized for Perplexity's citation style (heavy on named sources, dense stats) isn't identical to one optimized for ChatGPT's conversational synthesis. Second, methodology transparency is thin across the board. Only Frase and Context.dev publish anything close to a rubric explaining how their number is calculated; the rest ask you to trust a black box.
None of these eight tools, as far as their public documentation shows, actually query live ChatGPT, Perplexity, or Gemini sessions to check whether your page gets cited. They audit the page. That distinction matters enough that it gets its own section below.
Why the Same Page Gets Different Scores on Different Checkers
The core reason: there is no shared industry standard for what a GEO score measures or how it's weighted. Unlike, say, Google's Core Web Vitals, which have published thresholds (LCP under 2.5 seconds is "good," per web.dev To provide a good user experience, LCP should occur within 2.5 seconds of when the page first starts loading), GEO scoring is proprietary to each vendor. One tool might weight schema markup at 30% of the total score; another might weight it at 5% and put most of the weight on paragraph length.
This is the same problem the SEO industry had for years with "content scores" from tools like Clearscope or Surfer, each of which produces a different ideal word count and keyword density for the identical target keyword. GEO checkers inherited that same lack of standardization, just applied to a newer problem.
Practically, this means a 62 on one tool and a 62 on another are not the same 62. They're not measuring the same rubric, weighting the same factors, or even checking against the same reference set of "good" pages. If you're tracking progress over time, stick to one tool and treat the score as relative to itself, not as a universal grade you can compare against a competitor's score from a different checker.
How to Manually Verify Your AI Visibility
The only real way to confirm AI visibility is to ask the AI directly. Automated checkers grade your page's readiness; they don't confirm an actual citation happened. Here's the manual sanity-check workflow we use before trusting any automated score:
- Open ChatGPT (with browsing/search enabled) and ask the question your page targets, phrased the way a real user would ask it, not as your target keyword. "What's the best CRM for a 5-person agency" not "best CRM software."
- Repeat the identical prompt in Perplexity, which shows its sources inline, making it the easiest engine to check for direct citation.
- Try the same prompt in Google, checking whether an AI Overview appears and, if it does, whether your domain shows up in the linked sources beneath it.
- Run it once more in Gemini and Microsoft Copilot if your audience uses Microsoft 365 or Google Workspace search heavily, since citation behavior differs by engine.
- Log what actually got cited, your domain, a competitor, a Reddit thread, a Wikipedia page, and compare that against what your GEO score checker told you should happen.
Do this for your five highest-value target queries, not just your homepage keyword. If your GEO score is 78 but none of the five prompts surface your brand anywhere in the answer or the source list, the score was measuring readiness, not reality. That gap is normal and worth documenting, not panicking over.
What a Good GEO Score Means, and What It Doesn't Guarantee
A score above 70-85, depending on the tool's own scale, generally means your page has the structural bones an LLM can parse easily: clear answers, clean formatting, some citable data. That's genuinely useful. It does not mean you will get cited.
Here's the honest gap. LLM citation behavior depends on training data recency, the specific prompt phrasing, whether the engine is doing live retrieval or relying on parametric memory, and how many competing sources exist for that exact query. None of that is visible to a static content audit. A perfectly structured page on a low-authority, brand-new domain will likely lose out to a messier page on a domain the model already "trusts" from training exposure. Correlation between good structure and good citation rates exists, real practitioner testing backs that up, but it isn't causation, and no checker claims otherwise if you read their fine print instead of their homepage headline.
Treat a GEO score the way you'd treat a Flesch readability score: a useful proxy that flags obvious problems, not a prediction engine. Fix the things it flags. Don't assume fixing them buys you a citation.
Beyond a One-Off Score: Ongoing AI Visibility Monitoring
A single score is a snapshot; AI answers change week to week as models update and retrieval indexes refresh. If you only check once, you're optimizing for a moment in time that may not exist by the time you act on it.
When to graduate from a free checker to a monitoring platform
Move to continuous monitoring once you're tracking more than 5-10 target queries or care about competitive movement, not just your own page's static readiness. Monitoring platforms query live LLMs on a schedule and log whether your brand gets mentioned or cited, which is the actual signal a one-off score can't give you. Coverage of engines varies sharply across monitoring platforms: some track ChatGPT extensively but only a subset track Google's AI Overviews specifically. If Google AI Overviews visibility matters to your business, check that a monitoring tool actually covers it before subscribing. Geodeck's directory of AI visibility monitoring tools filters by which engines each one actually tracks.
When to bring in a GEO agency
Bring in an agency when the fixes a checker flags require ongoing content production or technical schema work you don't have the internal bandwidth for, not just a one-time cleanup. A checker can tell you your author bios lack E-E-A-T signals; it can't write 40 credible author bios for you or restructure a 200-page site's schema markup at scale. If the gap between "what the score says to fix" and "what your team can actually execute" is wide, that's the signal to look at Geodeck's list of GEO agencies rather than keep re-running free scans hoping the number moves on its own. For technical fixes you can handle in-house, like schema generation or structured data validation, our GEO and AEO tools directory and AI SEO content tools directory list options that don't require a developer for basic implementation.
FAQ
What is a good GEO score?
Most tools flag 70 or above as good and 85+ as strong, but that threshold is set by each vendor individually, not by any industry body. A 70 on one checker's scale isn't equivalent to a 70 on another's, so use the threshold as a rough internal benchmark, not a cross-tool standard.
Are GEO score checkers accurate?
They're accurate at what they actually measure: content structure, schema presence, and formatting heuristics. They are not accurate simulations of whether a real ChatGPT or Perplexity session will cite your page, since that depends on live retrieval, prompt phrasing, and model training data the checker never sees.
Is a GEO score checker free?
Most offer one free scan per URL, often gated behind an email signup, with deeper reports, historical tracking, or unlimited scans locked behind a paid plan. Of the eight tools compared above, all had some free option, but only geo-score.online and Glippy offered a scan with no email requirement at the time of testing.
How is a GEO score different from an SEO score?
An SEO score measures rankability, keyword usage, backlinks, technical crawlability, and page speed. A GEO score measures answer-extractability: whether an LLM can pull a clean, self-contained answer, a citable stat, or a structured fact from the page without additional context.
Do GEO score checkers test real AI citations?
No, most run a static audit of the page's HTML and text rather than querying a live LLM. A small number of dedicated AI visibility monitoring platforms do query real engines on a schedule to check for brand mentions, but that's a different product category than a free single-URL score checker.
Can I improve my GEO score without a developer?
Yes, for the content and structure layer: rewriting intros to lead with the answer, adding question-phrased headings, breaking up long paragraphs, and adding named sources to stats. Schema markup and an `llms.txt` file often need technical implementation, though basic FAQ schema can be added through most CMS plugins without custom code. Geodeck's GEO tools directory lists options for both the content side and the technical side.
Fact-checked against live sources, 2026-09-03: Verified GEO term origin (~2023, Princeton et al.), Core Web Vitals LCP "good" threshold (2.5s, web.dev), and Google's AI Overviews query-fan-out mechanism and its public stance that llms.txt isn't needed for AI search visibility (wording adjusted for accuracy); removed unverifiable proprietary Geodeck usage-percentage statistics (41%/77%/48%/64 tools) as unconfirmable and self-interested..