prompt-optimizer and PromptAgent
These are competitors—both provide automated prompt optimization capabilities, with the first offering a general-purpose prompt enhancement tool while the second implements a specialized multi-step planning approach (strategic planning with language models) to achieve expert-level optimization.
About prompt-optimizer
linshenkx/prompt-optimizer
一款提示词优化器，助力于编写高质量的提示词
Supports multi-model LLM backends (OpenAI, Gemini, DeepSeek, etc.) with dual optimization modes for system and user prompts, plus advanced testing via context variables, multi-turn sessions, and function calling. Available as web app, desktop client, Chrome extension, Docker container, and MCP server for Claude Desktop integration—with client-side data processing and optional password protection for secure deployment.
About PromptAgent
maitrix-org/PromptAgent
This is the official repo for "PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization". PromptAgent is a novel automatic prompt optimization method that autonomously crafts prompts equivalent in quality to those handcrafted by experts, i.e., expert-level prompts.
Employs Monte Carlo Tree Search (MCTS) to strategically sample model errors and iteratively refine prompts through reward simulation, unifying prompt sampling and evaluation in a single principled framework. Supports diverse model backends including OpenAI APIs, PaLM, Hugging Face text generation models, and vLLM for local inference, with YAML-based configuration for flexible experimentation. Integrates with BIG-bench tasks and the LLM Reasoners library, enabling optimization across reasoning and knowledge-intensive domains.
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