GuardAgent introduces a novel approach to LLM safety by creating a dedicated guard agent that dynamically monitors and evaluates the actions of target AI agents against custom safety requirements.

• Implements knowledge-enabled reasoning to analyze safety requests and generate protective guardrail code
• Moves beyond traditional text-based harm prevention to address complex interactive agent behaviors
• Includes the EICU-AC benchmark for medical applications, demonstrating cross-domain applicability
• Provides adaptive protection that evolves with the agent's behavior and environment

This research significantly advances AI safety in interactive contexts, allowing organizations to deploy autonomous LLM agents with greater confidence while maintaining compliance with specific security policies.

Original Paper: GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning