judgment-layer

Safety gating for autonomous agent actions is implemented by scoring operations on reversibility, bounded cost, and user observability to assign act-now, ask-first, or queue-for-review policies. This generates a judgment-policy.yaml and PreToolUse hook for runtime enforcement.

A PreToolUse hook for agent policy enforcement is a runtime gate that intercepts agent actions before execution, checking them against scoring criteria like reversibility and bounded cost to determine whether to execute, ask for confirmation, or queue for review.

You inventory agent actions to identify high-risk operations by cataloging skills and scoring each action across reversibility, bounded cost, and user observability, mapping high-risk results to a queue-for-review gating policy for safe automation.

Yes, you can generate a gating policy for Claude Code workflows by providing your agent's actions and desired authority levels. The process outputs a judgment-policy.yaml configuration and a judgment-gate.py script with a PreToolUse hook to enforce runtime gates.

Use ask-first versus queue-for-review gating based on action scoring: ask-first suits actions with moderate reversibility or bounded cost risks requiring user confirmation, while queue-for-review applies to high-risk operations needing offline evaluation before execution.

Yes, judgment-based action routing works without external dependencies by generating self-contained policy artifacts like judgment-policy.yaml and judgment-gate.py, which integrate directly into agent workflows via a PreToolUse hook configuration.