SidClaw

SidClaw provides the crucial approval and accountability layer for agentic AI, ensuring that every AI agent tool call is reviewed and logged. It works by intercepting agent actions, evaluating them against predefined policies, and, for high-risk scenarios, holding them for human review before execution. This robust system incorporates four core primitives: Identity (every agent has an owner and scoped permissions), Policy (every action is evaluated against explicit rules), Approval (high-risk actions receive human review with rich context), and Trace (every decision creates a tamper-proof audit log). By sitting at the tool-call layer, SidClaw offers a comprehensive solution for managing agent behavior in the real world.

Key Features

Use Cases