When building LLM agents, component interactions and scaffold compatibility matter more than individual module quality—AgentSpec provides tools to systematically test these combinations.
AgentSpec is a modular framework for building and understanding embodied AI agents by standardizing how components like memory, reasoning, and action execution connect. Instead of tightly coupled systems, it lets researchers swap components in and out to see how they interact, revealing that agent performance depends more on how modules work together than individual component strength.