This is a submission for the Built with Google Gemini: Writing Challenge
What I Built with Google Gemini
As a solo indie developer shipping iOS apps under my studio, Studio Rehoboth, I kept running into the same bottleneck every time I was ready to launch: App Store screenshots.
Apple requires very specific image dimensions (1284 x 2778 px for iPhone, 2048 x 2732 px for iPad), and making them look professional with device mockups, catchy headlines, and matching color palettes used to mean hours in Figma. For every single app. Every single update.
So I built AppStoreGenius: a personal AI-powered tool that turns my raw app screenshots into polished, Apple-compliant App Store assets in seconds. I built it directly in Google AI Studio using the Gemini API, and it's become an essential part of my development workflow.
Here's what it does:
AI-Powered Design Generation: I upload a raw screenshot of my app, and Gemini analyzes the image to automatically generate a marketing headline, descriptive subtitle, and a color palette (background + text colors) that matches the app's branding.
Smart Status Bar Masking: The AI identifies the exact color of the app's top navigation bar and applies a matching mask to hide the real status bar icons (battery, carrier, time), giving that clean, professional look.
Automatic Device Mockups: The screenshot gets placed inside a realistic device frame, complete with bezels and Dynamic Island for iPhone.
Full Customization + One-Click Export: I can tweak headlines, adjust backgrounds, change device types, and fine-tune positioning. When I'm happy with it, I export everything as high-resolution PNGs at Apple's exact required dimensions, packaged in a ZIP file.
I've used AppStoreGenius for two of my apps so far:
Lent Journey: A Catholic devotional app for Lent that hit #1 in the App Store for "lent." The professional-looking screenshots absolutely helped with conversions.
Advent Habit Calendar: A faith-based habit tracking app where I used the same workflow to generate App Store assets quickly.
Demo
The source code is on GitHub: github.com/mercyg/App-store-genius
It's built with TypeScript and React, generated from the google-gemini/aistudio-repository-template.
The tech stack:
- Frontend: TypeScript + React (Vite)
- AI: Google Gemini API for image analysis, headline generation, and color extraction
- Export: Client-side canvas rendering for pixel-perfect output at Apple's required dimensions
The tool isn't publicly deployed yet; right now, it's part of my personal development toolkit. But the code is open source if you want to see how it works under the hood.
What I Learned
The biggest lesson: AI tools are most powerful when they solve YOUR specific pain point. I didn't build AppStoreGenius as a product idea. I built it because I was tired of spending hours in Figma every time I shipped an app. The fact that it works so well is a testament to how capable the Gemini API is for practical, workflow-level automation.
Gemini's vision capabilities are genuinely impressive. The fact that it can analyze a screenshot, identify the dominant colors, understand the context of the app, and generate relevant marketing copy all from a single image upload still surprises me. The color extraction for status bar masking works remarkably well.
AI Studio made prototyping fast. Being able to iterate on prompts and build the tool directly in the AI Studio interface meant I went from idea to working app quickly. And now every time I need App Store screenshots, I just upload my raw screenshots, let Gemini do its thing, hit export, and get a ZIP file with everything at the exact dimensions Apple requires, ready to upload straight to App Store Connect.
Professional presentation matters more than you think. When I launched Lent Journey, I genuinely believe the polished App Store screenshots contributed to the strong conversion rate. People judge apps by their screenshots before they ever download, and having AI-generated professional assets lets me compete with apps that have dedicated design teams.
Google Gemini Feedback
What worked well:
The image analysis capabilities are the star here. Uploading a screenshot and getting back a coherent headline, subtitle, and color palette that actually matches the app's vibe — that's incredibly useful. For Lent Journey, it nailed the spiritual, contemplative tone. The color detection was accurate enough that the status bar mask blended seamlessly.
The AI Studio prototyping experience was also smooth. Being able to iterate on prompts and see results immediately, then export to a proper codebase, meant I went from idea to working tool faster than I expected.
Where I ran into friction:
Getting the exact output format right took multiple iterations of prompting. Apple's requirements are very specific — exact pixel dimensions, exact aspect ratios — and the initial prompts didn't always respect those constraints. I had to be very explicit about the output specifications, which required some back-and-forth.
The Gemini API sometimes generated headlines that were a bit generic or didn't quite capture the unique value proposition of the app. It's great as a starting point, but I almost always tweaked the generated copy. This is fine for my workflow since the tool supports manual editing, but the AI-generated marketing copy does need a human eye.
Overall, Gemini is at its best when you give it a focused, well-defined task, analyze this image, extract these colors, generate a headline in this style — rather than asking it to handle the entire creative process end-to-end. That's exactly how I architected AppStoreGenius, and it works beautifully.
I'm considering publishing AppStoreGenius as a tool that other indie devs can use. If that's something you'd find useful, let me know in the comments! And if you've built something cool with Gemini, I'd love to hear about it.
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