StoreScribe: an open model writes your App Store listing, inside every limit

说明与用途

StoreScribe 自动化创建 App Store 和 Google Play 列表，确保符合所有字符和字节限制，使用 Gemma 4 和竞争对手研究。

问题

Indie app developers and small studios struggle to create compliant App Store and Google Play listings within strict character and byte limits, often spending time on manual research and formatting.

结果

StoreScribe reduces listing creation time from hours to minutes, ensures compliance with all store limits, and provides competitor‑informed keyword optimization across multiple languages.

工作流

• Read project metadata (Info.plist, pubspec.yaml, app.json, README, screenshots)
• Extract app name, bundle ID, screen names, current fastlane listing
• Use Gemma 4 to draft listing fields
• Run limits.js to measure fields per store rules
• If over limit, send back to Gemma with exact count for tightening
• Trim cleanly at word boundary if needed
• Pack keywords by removing duplicates, plurals, competitor brands, and fitting into 100 bytes
• Localize keywords for each target market
• Export listings to fastlane/metadata
• Track keyword rank daily via Tiger Data
• Allow live editing with character counters

证据

StoreScribe writes your App Store and Google Play listings, researched against the apps you're competing with, inside every character limit, in up to six languages.

来源

The code is done, the screenshots are done, and then App Store Connect asks for: an app name in 30 characters, a subtitle in 30 characters, a keywords field of 100 bytes.

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I build mobile apps, and the part I always put off is the store listing.

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The model writes, the code decides. Language models are bad at counting characters, and worse at counting UTF-8 bytes.

来源

It reads the project itself: the app name and bundle id from Info.plist, pubspec.yaml or app.json, the README, the names of the screens in your code, your current fastlane listing and any screenshots it can find.

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