This project implements a robust permission enforcement system for an AI agent, acting as the central gatekeeper for all tool executions. It evaluates actions against a hierarchy of security checks: explicit static rules, the agent's current operating mode (e.g., Auto vs. Plan), and strict filesystem sandboxing. When executed in autonomous modes, it leverages an AI classifier to judge the safety of ambiguous commands based on conversation context.
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