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Grail-Tracker

  • 2 Devlogs
  • 2 Total hours

Grail Tracker is an AI-powered digital wardrobe assistant designed to organize your clothes and style your outfits instantly. Users snap a photo of any clothing item in their possession, and the app uses computer vision to automatically categorize it into Shirts, Pants, Sneakers, or Outerwear. From there, the app asks a few brief, personalized styling questions to instantly generate the perfect outfit combination from your active closet.

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I made an app called Grail-Tracker. Where you can insert clothing items from your wardrobe and it will generate you outfits based on your preferences of color palettes, vibes, etc. Here is a Vercel link to my project: https://grail-tracker.vercel.app/. There is no api or backend installed yet so there won’t be any computing, just a frontend.

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🛠️ What did you make?
I built Grail Tracker, which is a fast mobile app for tracking and cataloging high-value collectibles or milestones (your "grails"). Spreadsheets are super annoying to look at, so I made a clean card layout where you can see the item name, description, rarity tier, and timestamp all at a glance. It also saves everything directly to your device's memory, so your list doesn't disappear when you close the app.

🧠 What was challenging?
The hardest part was definitely getting the local saving feature to work right without breaking the app's layout. At first, when I tried passing data around, the UI completely glitched out—buttons were overlapping and clipping behind other elements on the screen. I had to figure out how to make async storage and JSON payloads load up properly on startup, while fixing a bunch of messy CSS flexbox rules so the screen scales normally.

🏆 What are you proud of?
I'm proud of how I used a "vibe coding" setup with Cursor, Claude, and v0 to build this. I acted as the main builder and designer—I chose the style, put all the separate code pieces together, and handled the whole GitHub setup—but I used AI like an assistant to quickly generate the basic layouts and help me look up weird syntax errors. Doing it this way let me ship a fully working app with saving features way faster than doing it completely from scratch.

🧪 What should people know so they can test the project?
Since the app saves everything locally on your device, the best way to see how it works is to watch the short video demo I attached! If you want to check out the actual files or see my hour-by-hour progress, you can look through the public GitHub repo.

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