Prompter Dock
100% local prompt organizer & global HUD for AI power users
10 followers
100% local prompt organizer & global HUD for AI power users
10 followers
Tired of copy-pasting prompts? Prompter Dock gives you a private, offline prompt organizer with a global Spotlight-style HUD. Access your prompts instantly inside any app, chain prompts to automate workflows, and improve them using a bundled local LLM.
Interactive
Free Options
Launch Team / Built With
How does the bundled local LLM actually perform for refining complex prompts, like compared to running something through GPT-4 in the cloud?
@anlcengi7zjn Fantastic question! I tried giving this local LLM several different raw prompts to generate improved prompts during testing. I gave it prompts for the same task at three different levels:
1. No context
e.g. Build a fully featured calculator app.
2. Low context
e.g. Build a fully featured calculator app. Implement a clean, responsive UI with standard arithmetic (+, −, ×, ÷), decimal support, parentheses, percentage, sign toggle (±), memory functions (MC, MR, M+, M−), clear (C/AC), backspace, keyboard shortcuts, calculation history, error handling, and dark/light mode. Structure the project with maintainable, modular code, include tests where appropriate, and ensure the app is production-ready with good UX and accessibility.
3. High context
e.g. Build a production-ready calculator app using React + TypeScript + Vite and Tailwind CSS. Use Zustand for state management and Vitest for testing. Create a responsive, accessible UI with dark/light mode, keyboard shortcuts, standard arithmetic, parentheses, percentage, ±, memory (MC/MR/M+/M−), backspace, AC/C, calculation history (persisted in localStorage), configurable precision, and robust error handling. Organize the code with feature-based architecture, reusable components, custom hooks, and utility modules. Follow clean code principles, strict TypeScript, ESLint + Prettier, and include unit tests, README, and complete project structure.
I can assure you that the local LLM was surprisingly good for its size. The system prompt is highly optimized and the model creates fantastic results even with low context. Also, it is worth noting that very long prompts and too much context degrades any model's performance. The trick is to give the right amount of information.
The offline Spotlight-style HUD actually pops up faster than the cloud alternatives I have tried, and chaining prompts together for repetitive tasks is genuinely useful. Nice to see a local LLM included too, no data leaving the machine.
Spotlight-style HUD for prompts is a great idea, especially the offline angle. The chaining feature feels like it could seriously speed up repetitive writing tasks I do all day.
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