AgentWall: A Runtime Safety Layer for Local AI Agents

In three linesAgentWall is a runtime safety layer for local AI agents. It intercepts proposed agent actions before execution, evaluates them against an explicit declarative policy, requires human approval for sensitive operations, and records a complete audit trail. Implemented as an MCP-enforcing proxy and native OpenClaw plugin, it achieves 92.9% policy enforcement accuracy with sub-millisecond overhead.

Summary generated by Claude — human-verified