📄 中文摘要
许多开发者在部署AI代理时常常遇到相似的问题：代理在初期表现良好，但很快就失去了个性，开始出现泛化响应或忽略预设约束等情况。尝试过多种方法，如调整系统提示的长度、使用不同的数据格式和示例，但都未能解决问题。最终，作者创建了一个新的框架，旨在帮助开发者构建更有效的AI代理，确保其在长时间内保持一致性和个性化。这个框架的核心在于重新审视和优化代理的核心配置文件，从而提升其稳定性和表现。
停止像2023年那样编写AI代理提示：让你的OpenClaw代理真正工作的框架
📄 English Summary
Stop Writing AI Agent Prompts Like It's 2023: The Framework That Makes Your OpenClaw Agent Actually Work
Many developers encounter similar issues when deploying AI agents: the agents perform well initially but quickly lose their character, leading to generic responses or ignoring predefined constraints. Various attempts to resolve these issues, such as adjusting the length of system prompts, using different data formats, and providing more or fewer examples, have proven ineffective. Ultimately, the author developed a new framework aimed at helping developers create more effective AI agents, ensuring they maintain consistency and personality over time. The core of this framework lies in re-evaluating and optimizing the agent's core configuration file to enhance its stability and performance.