This seems like a perfect use case for a local model. But I've found in practice that the system requirements for agents are much higher than for models that can handle simple refactoring tasks. Once tool use context is factored in, there is very little room for models that perform decently.

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musesum 2 hours ago | parent [-]

What I hope to do with refactoring is to distill namespace and common patterns into a DSL. I am very curious about what tradeoffs you found.

	▲	reedlaw an hour ago \| parent [-]
		Whatever agent I tried would include thousands of tokens in tool-use instruction. That would use up most available context unless running very low-spec models. I've concluded it's best to use the big 3 for most tasks and qwen on runpod for more private data.