Paper2Agent: Stanford Reimagining Research Papers as Interactive AI Agents

I went looking for how they define "agent" in the paper:

> AI agents are autonomous systems that can reason about tasks and act to achieve goals by leveraging external tools and resources [4]. Modern AI agents are typically powered by large language models (LLMs) connected to external tools or APIs. They can perform reasoning, invoke specialized models, and adapt based on feedback [5]. Agents differ from static models in that they are interactive and adaptive. Rather than returning fixed outputs, they can take multi-step actions, integrate context, and support iterative human–AI collaboration. Importantly, because agents are built on top of LLMs, users can interact with agents through human language, substantially reducing usage barriers for scientists.

So more-or-less an LLM running tools in a loop. I'm guessing "invoke specialized models" is achieved here by running a tool call against some other model.

With your definitions of agents as running tools in a loop, do you have high hopes for multi-tool agents being feasible from a security perspective? Seems like they'll need to be locked down