请问HN：有哪些可以协作的多大型语言模型（Multi-LLM）调度框架？
我的总体看法是：双子座在高层次的重构方面表现出色，但在实际编码时却充满了漏洞。另一方面，GPT/Claude在编码方面表现优异，但在重构时往往只进行小修小补。他们喜欢加入不必要的防御性编程，以保持向后兼容性，结果往往导致冗长的杂乱代码。
我的想法是发挥他们的优势：让双子座提供方向性和架构性的思路，然后让GPT/Claude进行讨论和实现（实际上，我一直在手动进行这样的操作，效果相当不错）。
所以我的问题是：有没有能够有效自动化这种协作的Agent框架？
我很清楚现有的“子代理”功能，但根据我的经验，AI并不总是选择调用它们。此外，当子代理在工作时，主模型通常只是闲置着。这让我觉得这不太像真正的协作，更像是一种机制，用来防止外包任务污染主上下文——至少在我看来是这样的。
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Here is my general take: I feel Gemini is excellent at high-level refactoring but riddled with bugs when writing actual code. On the other hand, GPT/Claude excel at coding, but when it comes to refactoring, they tend to stick to minor patches. They love throwing in unnecessary defensive programming just to maintain backward compatibility, or ending up with verbose spaghetti code.<p>My idea is to complement their strengths: let Gemini provide the directional/architectural ideas, and then have GPT/Claude discuss and implement them (in fact, I do this manually all the time, and the results are pretty good).<p>So my question is: Are there any Agent frameworks that can automate this kind of collaboration effectively?<p>I'm well aware of the existing "subagent" features, but in my experience, the AI doesn't always choose to invoke them. Moreover, while the subagent is working, the main model usually just sits there idling. It feels less like actual collaboration and more like a mechanism to prevent outsourced tasks from polluting the main context—at least, that's how it feels to me.