📄 中文摘要
在面对多个提示变体时，选择最佳的提示通常依赖于人工测试，这种方法只能提供主观感受而非数据支持。为了解决这一问题，可以使用一个简单的 Python 工具来高效测试提示。通过安装必要的库并克隆指定的 GitHub 仓库，用户可以快速设置并定义不同的提示变体。接下来，通过创建 YAML 文件来组织这些变体，从而实现系统化的测试，获取更可靠的数据结果。这种方法不仅节省时间，还能提高提示优化的准确性。
停止猜测哪个 LLM 提示效果最佳 — 测试它们（免费 Python 工具）
出处: Stop Guessing Which LLM Prompt Works Best — Test Them (Free Python Tool)
发布: 2026年3月11日
📄 English Summary
Stop Guessing Which LLM Prompt Works Best — Test Them (Free Python Tool)
Choosing the best prompt among several variations often relies on manual testing, which provides subjective impressions rather than data-driven insights. To address this issue, a simple Python tool can efficiently test prompts. By installing the necessary libraries and cloning a specified GitHub repository, users can quickly set up and define different prompt variations. Subsequently, creating a YAML file organizes these variations for systematic testing, yielding more reliable data results. This approach saves time and enhances the accuracy of prompt optimization.