The library implements a simple agent framework controlled by large language models. It uses a loop of Thought, Action, and Observation where the LLM decides which tools to use based on the task. Pre-built tools include Python code execution, Google search, and Hacker News search. The project serves as an educational implementation inspired by LangChain, aimed at understanding agent mechanics in minimal code.