# The six kinds of pages LLMs actually cite (and how to find yours in an afternoon)

> Source: <https://dev.to/dongdongdev/the-six-kinds-of-pages-llms-actually-cite-and-how-to-find-yours-in-an-afternoon-8i1>
> Published: 2026-11-10 05:09:13+00:00

Last time I wrote about [auditing whether AI mentions your brand](https://dev.to/dongdongdev/your-product-doesnt-exist-to-chatgpt-a-20-minute-ai-visibility-audit-you-can-run-yourself-3ki1). The part people ask about is always the same: **which pages get cited, and how do I get on them?**

Here's the short version: run your buyer prompts, collect every URL the answer cites, and cluster them. In every audit I've done, the citations fall into six buckets. Your job is to find the buckets where you're absent *but reachable*.

Twelve prompts, four families: category, problem, comparison, brand. Run them in ChatGPT (with search), Perplexity and Gemini, logged out. Copy every source URL each answer cites into one column. Don't judge yet, just collect — 60 to 100 rows is normal.

Every URL will land in one of these:

| Bucket | What it looks like | How you get in | 
|---|---|---|
| **Directories** | "Top 40 AI tools", niche tool indexes | Free/paid submission forms | 
| **Listicles & comparisons** | "Best X for Y in 2026", "A vs B" | Pitch the author, or publish your own comparison page | 
| **Docs & changelogs** | Product docs, release notes, pricing pages | Yours to write — make one page answer one question | 
| **Community threads** | Reddit, Quora, HN, Indie Hackers, forums | Answer real questions, disclose you're the maker | 
| **News & editorial** | Trade press, launch coverage | Harder; usually needs a story, not a product | 
| **Code & lists** | GitHub repos, awesome-lists, package docs | A PR, if your tool is developer-adjacent | 

Count rows per bucket. Two patterns come up constantly:

Now compare with where you actually exist. The gap list is your roadmap — and it's usually shorter than it feels.

Before any of this works, two things are often quietly broken:

`robots.txt` for `GPTBot`, `ClaudeBot`, `PerplexityBot`, `Google-Extended`. Plenty of sites block them by accident via a copied template. Two years of content behind a crawler block is a common, embarrassing finding.
The failure mode is trying all six at once. I'd pick: one directory pass (10 submissions), one community pass (3 thoughtful answers, disclosure included), and one content pass (5 answer-shaped pages — one question per page, answer in the first 40 words).

Then re-run the same twelve prompts two to four weeks later and count the same buckets. If the distribution shifted toward sources you control, it's working. If it didn't, you were probably working on the wrong bucket — which is exactly the thing measurement is for.

If you'd rather not build the spreadsheet, I made [bidvix](https://bidvix.com/?utm_source=devto&utm_medium=article&utm_campaign=launch-phase1) for the measurement half (mention rate + cited URLs across five models). The clustering above is the part that actually changes what you do, and it works fine in a notebook.