Can I test how my site appears in ChatGPT, Claude or other LLMs?

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In short, yes, you can test how hour site appears in Large Language Models (LLMs). But with important caveats. Maybe we reframe the question and ask, ‘how does my content look through the lens of an AI assistant?’ rather than try and hunt down a literal snapshot.

Let’s start with some background:

Read time: 3 minutes

Do you really need to test how your site appears in LLMs?

Your site content isn’t just read by humans, you know that. Bots have been crawling sites for decades. But more and more it’s being ingested by large language models (LLMs) to answer questions … from ‘which boots are best for trekking in the Pennines?’ to ‘write me a brief biography of Jane Austen’, AI engines such as ChatGPT, Perplexity, and CoPilot are fast becoming the first stop for a quick and complete answer.

If your pages parse poorly (maybe because of poorly structured metadata, vague headings, or hidden content), the AI may misinterpret or omit your valuable information. And then you will fail to show up in the answers.

Testing how your site appears in LLMs can reveal vital GEO, SEO, UX, or content gaps.

What does ‘testing’ how your site appears to LLMs really mean?

LLMs don’t render a page visually like a browser. Instead, they fetch your text, tags, headings, metadata, and potentially crawl your site (if the model has browsing capability or plugins). They parse the content as structured data + natural language, and then decide what to include in their responses.

Because of this, ‘what appears in ChatGPT’ can depend heavily on:

Whether ChatGPT (or whichever LLM) has web browsing/plugin access enabled
Whether that model is permitted to crawl your site
How your site is built (are there JavaScript-heavy pages and hidden content. Dynamic loading can also be invisible to bots)
How well your content is structured (does it have clear headings, alt text, meta descriptions)

How should you test how your site appears in LLMs, in practice

Here’s a non-technical run down:

Use ChatGPT (with browsing / plugin turned on)

In settings, enable “beta/web browsing/plugins” mode. This allows some versions of ChatGPT to fetch real web pages.
Then prompt: ‘Please fetch and summarise [your URL]. What are the main headings, keywords, and what content did you skip or could not read?’

Prompt Claude, Co-Pilot, Perplexity

Give them the same prompt. If they have web access, ask ‘crawl this URL’ or ‘summarise from [site]’ and look at what sections they capture or omit.

Compare against your page HTML

View the page source (browser>View Source) or use SEO tools to inspect your headings, metadata, and structured data (schema). See whether elements that your LLM summaries captured or missed map to your heading/meta structure.

Iterate & re-test

If AI models omit a section (for example your ‘Case Studies’ or ‘Team bios’), check whether that content is behind tabs, loaded async, or lost in generic prose. Adjust your content so that your content is clean, plain-text, and well-labelled…and test again.

Limitations & expectations

Not all LLMs have live web access. Some can only rely on their training data (i.e. they have ‘knowledge cutoffs’). Remember that, if they can’t crawl your site, the test won’t give you an accurate, up to date report.
AI models might choose to omit sections they deem low relevance. That’s a signal to you to consider whether those omitted pieces of content are truly core to your message?
Some pages are technically readable but undesirable (they may be low quality, or duplicate content) and this may mean they have been suppressed by the AI’s heuristics.

What conclusions should you draw from your LLM tests?

Missing or truncated content means… it may be time to rethink your page structure (such as ensuring clear H2/H3 headings, and avoid hidden tabs)
Irrelevant keywords or focus means… your framing or semantic emphasis may need tweaking
Inconsistent results across models mean… you need to prioritise consistency and clarity in core messaging

You absolutely can approximate how your content looks through the eyes of ChatGPT, Claude, Perplexity, etc, but you are not going to be able to see literal screenshots. Rather you will be able to run structured parsing experiments. Get clever using prompt tests, compare output vs. your real page structure, iterate, and you’ll gradually align your content for both human and AI consumption.
Or better still. Take a GEO strategy that encompasses quality tracking tools (like Otterly.ai) to measure visibility in AI search and targeted content optimising activities to gain greater and greater traction overtime.

About the author

GEO Expert & Frontier15 Founder

Jo Robb

Jo is the founder of Frontier15, where she helps brands stay visible in the age of AI search. With 25 years working in digital and over a decade focused on writing and strategising for technology and brand clients, she’s become obsessed with how content performs in generative search… and what that means for the future of brand visibility.

What we do

Frontier15 helps brands achieve visibility in the era of AI search, creating content strategies that make your expertise discoverable and trusted by both people and machines. Get in touch and ask us how we can map a GEO-informed content strategy that helps future-proof your brand.

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Can I test how my site appears in ChatGPT, Claude, Co-Pilot, Perplexity or other LLMs?