Make your app
visible to ChatGPT.

You shipped on Lovable, Bolt, v0, Base44 or Replit. It looks great — then someone asks ChatGPT for “an app that does X” and it recommends a competitor that has never heard of you. That's not bad luck: AI assistants recommend what they can read and verify, and most AI-built apps ship as a JavaScript shell with almost no machine-readable facts. Here's exactly what to fix.

Why isn't my app showing up when people ask ChatGPT for one like it?

Almost always because AI engines can't read it. A Lovable, Bolt, v0 or Replit app usually ships as a JavaScript shell with little server-rendered text, no JSON-LD facts, no /llms.txt, and no clean heading outline. So when a model is asked 'what's a good app for X?', it has nothing about you to extract and names a competitor that explains itself. The fix is to make your app legible: add the machine-readable facts and structure answer engines read first.

The fix isn't to make your app prettier — it's to make it legible: add the machine-readable facts and structure answer engines read first.

What are the 9 signals AI engines read?

getAdvantage's Get Found engine scores the same signals an answer engine relies on. You can work through them by hand:

1. <title> — a clear, descriptive page title that says what your app is.
2. Meta description — a concise summary AI can quote as your one-liner.
3. JSON-LD structured data — a hidden, machine-readable fact sheet about your app. The single highest-leverage fix.
4. Headings — a single sensible <h1> plus a logical heading structure, so the page has a readable outline.
5. /llms.txt — a plain-text introduction file that hands AI a clean map of your app.
6. Content-to-markup ratio — enough real, server-rendered text. A page that's all design and no words reads nearly blank to AI.
7. Open Graph — the OG tags that describe your page when it's shared and parsed.
8. Canonical — a canonical URL so AI knows the authoritative version of a page.
9. AI-crawler access — whether crawlers like GPTBot, ClaudeBot and PerplexityBot are actually allowed in robots.txt.

What is an llms.txt file and does my app need one?

/llms.txt is an emerging standard — a plain-text file at yourapp.com/llms.txt that gives AI a clean, curated summary of what your app is and which pages matter. A good one follows the llmstxt.org shape (this is the pattern getAdvantage publishes for itself at getadvantage.app/llms.txt):

# Your App Name

> One-sentence summary of what your app does and who it's for.

## Key pages

- [Home](https://yourapp.com/): What the app is.
- [Pricing](https://yourapp.com/pricing): Plans and prices.
- [Docs](https://yourapp.com/docs): How it works.

Serve it as text/plain so crawlers read it as a real file, not an HTML shell.

How do I add JSON-LD structured data to a vibe-coded app?

JSON-LD is a small block of structured, machine-readable facts — your app's name, what it does, what it costs, who it's for — in schema.org's format, dropped into your page's HTML. You don't have to hand-write it. The fastest path on an AI builder is to describe what you want and let the builder write it — for example:

Add a <script type="application/ld+json"> block to my homepage with
schema.org structured data describing this app: [name], [one-line
description], [pricing], [primary category]. Use the
SoftwareApplication or Product type.

Your builder writes the JSON-LD for you — no manual code editing. (getAdvantage generates this exact block from your app's own content and hands it back as a paste-ready prompt.)

How do I let AI crawlers read my app?

Check your robots.txt and make sure you're not blocking the crawlers answer engines use — at minimum GPTBot (OpenAI), ClaudeBot (Anthropic) and PerplexityBot. A blanket disallow, or a default that blocks them, means the model literally cannot read your app, and no amount of on-page work helps if the crawler is turned away at the door.

Do I have to edit code to make my app visible to AI?

No. On Lovable, Bolt, v0, Base44 or Replit every one of these fixes can be expressed as a prompt your builder turns into code — JSON-LD, meta tags, headings and FAQ schema included. The two file-based fixes, llms.txt and robots.txt, are real files a browser script can't create, so you publish those by dropping the exact contents at the right path. None of it requires writing code by hand.

How do I check whether it worked?

Re-read your app the way AI does and confirm the signals are present — or run a scan that measures all 9at once. getAdvantage's free Get Found scan fetches your live app, scores the signals, shows which competitors a ChatGPT-class model names instead of you, and hands you each remaining fix as a prompt for your builder. It's a real measurement of observable signals at scan time — not a guarantee of any AI's answer, because no one controls that. What it does guarantee is that you'll know precisely what's missing.