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I built AI Prompt Vault because the prompts I reused while coding and writing documentation were scattered across desktop Markdown files, phone notes, and email drafts. When I needed a prompt that had worked a week earlier, finding it took longer than it should. I wanted a searchable Android library that kept prompts on the device and made them quick to copy.
The problem: prompts were easy to lose
Tools such as ChatGPT, Claude, and Gemini had become part of my work, but the prompts I wanted to reuse did not live in one place. Some were on my computer, some in notes on my phone, and others in email drafts. That fragmentation made retrieval the problem: remembering that a useful prompt existed did not mean I could find it when I needed it.
AI Prompt Vault was my attempt to solve that personal workflow problem. It is an Android app for saving prompts in a local library, searching them, filtering by category, and copying one to the clipboard with a tap. This is the motivation behind my project, not a claim that every AI user has the same problem.
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I initially considered Firebase authentication and synchronization across devices, then dropped the sync plan. I did not want the core task—saving and retrieving a prompt—to require another account. I also wanted to prioritize privacy and speed in the app’s design.
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That choice has a clear tradeoff. Local storage avoids making a cloud service and sign-in part of the basic workflow, but it does not establish that prompts are automatically available on another device. The account of the app does not describe a cross-device backup or recovery feature, so users would need to consider how they would preserve their library if they changed or lost a phone. Nor is local storage, by itself, proof that an app is more secure; no security assessment or measured performance comparison is reported.
How the Android app is put together
Room stores the prompt library
I used Kotlin, Jetpack Compose, Room, and Hilt. Room provides the app’s local database, so prompts are stored on the device rather than requiring a backend for the library’s basic operations.
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FTS4 searches titles and prompt text
A prompt is only useful if it can be found again. I integrated SQLite FTS4 through Room to search both prompt titles and their bodies. This was my way of supporting full-text search without introducing a server-side search dependency. The project account describes the implementation but does not provide an independent benchmark, so it does not establish a particular search speed.
One state flow keeps the interface coordinated
I used an MVI approach: a ViewModel exposes immutable state, and Room’s Flow integration lets the interface react to database changes. That structure is intended to keep related interface state—such as a search query, selected category, and visible list—predictable as the user interacts with the library.
Rank #3
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Clipboard copying is part of the core workflow
The app uses Android’s ClipboardManager for its one-tap copy action. Clipboard behavior is partly controlled by Android itself; the project account specifically notes the clipboard overlay introduced in Android 13. That means a copy interaction has to work with the platform’s UI behavior rather than treating the clipboard as an invisible, app-only feature.
What I learned from the tradeoffs
- Search needs to cover the prompt itself. Searching only titles would leave users dependent on remembering how they named each entry, so I included prompt bodies in the FTS4 search.
- Removing sync reduces scope but leaves backup unanswered. Skipping Firebase avoids building account and synchronization flows, while the available account of the app does not establish a backup or recovery path.
- Clipboard behavior belongs in the design. Copying is central to the product, and Android’s own clipboard interface affects what users see after they tap.
- Variable inputs remain a work in progress. I identified handling placeholders such as “Insert code here” as an area still being refined. The app should not be described as having a finished prompt-variable system.
Who this design may suit
A local-first prompt library makes sense for the workflow I was trying to improve: keeping reusable text organized and retrievable on an Android phone without making an account or depending on a cloud service for ordinary access. It is less obviously suitable for someone who needs the same library synchronized across multiple devices or expects a built-in recovery mechanism. Those needs depend on backup and sync behavior that the project account does not establish.
Quick Recap
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