The Prompt Optimizer repository is a TypeScript-based AI tool designed to help users write better prompts and achieve improved results from AI models. Hosted at https://prompt.always200.com, it provides a comprehensive platform for prompt optimization, testing, and evaluation across multiple deployment formats including web applications, desktop applications, Chrome extensions, and Docker containers.
The core functionality centers on intelligent prompt optimization through one-click processing with multi-round iterative improvements. The tool supports dual-mode optimization, allowing users to optimize both system prompts and user prompts depending on their specific use case. A key differentiator is the analysis and comparison evaluation system, which enables users to assess whether optimizations have genuinely improved prompt performance through single-result evaluation and multi-result comparative analysis.
The repository demonstrates broad model integration capabilities, supporting mainstream AI providers including OpenAI, Gemini, DeepSeek, Grok, Zhipu AI, SiliconFlow, and MiniMax. Beyond text-based optimization, the tool includes sophisticated image generation features supporting Text-to-Image, Image-to-Image, and Multi-Image generation modes with models like Gemini, Seedream, and Grok, complete with model-specific parameter configuration and style transfer capabilities.
Prompt sourcing flexibility is built into the design, allowing users to begin with manual writing, templates, local file imports, or integration with Prompt Garden. The Smart Favorites system enables users to save optimized prompts as reusable assets with version history, reproducible examples, media support, and source binding to track prompt origins. Advanced testing capabilities include context variable management, multi-turn conversation simulation, and Function Calling support for both OpenAI and Gemini.
Security and privacy are prioritized through pure client-side processing architecture where data interactions occur directly between the user and AI service providers, bypassing intermediate servers. The platform includes password protection features for secure deployment scenarios. The tool also supports the Model Context Protocol, enabling integration with MCP-compatible applications like Claude Desktop.
The project supports multiple deployment pathways including one-click Vercel deployment, Cloudflare Pages deployment with Workers Builds, and manual Docker deployment. Desktop applications are available as both installers with automatic update capability and archives, with the desktop version offering advantages including elimination of CORS limitations for direct API connections to services like locally deployed Ollama and improved performance through native operation without browser dependency.
