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While model and agent evaluation are inextricably linked, their technical benchmarks and metrics for success are fundamentally different.

Using the toolkit for this specific use case provides multiple benefits: Config-driven workflows The toolkit helps shift the project from a rigid script to a flexible research platform. Instead of hard-coding the interactions between agents, you define the system’s logic—including personas, tools, and constraints—entirely within a YAML configuration. This modularity makes it trivial to swap models for different tasks. For example, you can assign a high-reasoning model to handle hypothesis generation while using a faster, more cost-effective model for the code agent without modifying the underl