App Store Optimization for apps built with Cursor

Cursor is not a no-code app builder. It is a genuine code editor, a fork of VS Code, where an AI agent writes and edits real source across your whole project. Most people building mobile apps in Cursor use React Native with Expo, and Expo publishes an official Cursor integration: the agent can read your project’s AGENTS.md, pull Expo documentation through the Expo MCP server, and help manage your EAS build and submit workflow. The output is a real, cross-platform codebase that installs on iOS and Android, not a web wrapper.

That strength is also where the gap opens. Cursor can carry you from an idea to a signed build sitting in App Store Connect and the Play Console, and then it stops. It does not research what your users search, it does not write a title tuned to those searches, and it never fills the keyword field Apple hides behind the listing. Your app is live and technically clean, and completely invisible, because ranking is a text-and-behavior problem the code editor was never designed to solve.

Once your Cursor app is live, discovery runs on metadata you have to write by hand. Apple says its search results are based on text relevance (matches for your app’s title, subtitle, keywords, and primary category) plus user behavior like downloads, ratings, and reviews. Apple does not index your description for search, so long marketing copy pasted into that field does nothing for rankings; the work happens in the 30-character app name, the 30-character subtitle, and the hidden 100-character keyword field.

Google Play works differently. Your title, short description (80 characters), and full description (4,000 characters) all feed discoverability, layered on top of ratings, reviews, and downloads. So the same app needs two distinct metadata jobs: a byte-tight, keyword-first set of fields on iOS, and a fuller but still-focused write-up on Android. None of this exists until you create it, and a default title left as your Cursor project name is the single most common reason a good app never gets found.

• iOS search: app name + subtitle + keyword field + primary category are indexed; the description is not.
• Google Play search: title + short description + long description all count.
• Ratings, reviews, and downloads feed rank on both stores, and a good listing earns the installs that compound.

Building fast with AI cuts both ways at review time. Apple’s guidelines reject apps that are low-quality, untested, or incomplete (Guideline 4.2, minimum functionality), and they reject apps that share a similar binary, metadata, or concept with other apps with only minor differences (Guideline 4.3, spam). An app assembled carelessly, or a dozen near-identical apps spun out of the same prompt, is exactly what those rules exist to catch. This is not a reason to avoid building with Cursor; it is a reason to finish the app into something genuinely complete and useful, and to describe it honestly.

A well-optimized listing is how you prove that. Accurate, specific metadata (Guideline 2.3) signals a real product to both the reviewer and the user: a title and subtitle that say precisely what the app does, screenshots that show the real experience, and a keyword set matched to how people actually search. You cannot buy your way up the organic rankings, and no ASO tactic changes the code Cursor wrote. What a strong listing does is make sure the genuine app you built is found by the people already searching for what it does.

The fix is a repeatable ASO pass that lives next to your Cursor workflow rather than replacing it. Start by finding the specific terms your users actually type: not the abstract category, but the job your app does. Then weigh each by how much it is searched against how hard it is to rank, per store and per market. Place your strongest terms where each store indexes them, write a subtitle and short description that read like a human wrote them, and lead your screenshots with the outcome so the impressions you earn convert into installs.

Because Cursor supports project skills and agent instructions, you can pull this work into the editor itself: ASOScan publishes a free, open-source ASO Skill for Cursor and Claude Code, so the same environment that wrote your app can help draft and check its listing. From there, a free 60-second scan shows what your current listing is missing, and AI-generated metadata in your app’s target language gives you a first draft to refine. That is the discovery half of the build the code editor left undone.

• Research keywords by search demand vs difficulty, per store and per market, owning the job your app does rather than the category word.
• Place terms where each store indexes them: iOS title / subtitle / keyword field; Android title / short / long description.
• Use the free ASO Skill inside Cursor, then a free listing scan and AI-drafted metadata to close the gap.

A repeatable pass that adds the discovery layer Cursor leaves out, without changing how you build.