prevention-rules

Block risky AI agent actions by generating prevention rules from recurring failure patterns. The system validates proposed tool calls against an active rule set and reviews promotion history to ensure non-compliant behaviors are stopped before execution.

Compliance automation pattern matching checks proposed agent actions against active prevention rules to identify restricted behaviors. It validates tool calls by comparing action descriptions to enforced match patterns and returns the specific rule causing a block.

You can trace agent governance rule promotions by inspecting feedback events stored in the audit trail. The system records which originating incidents caused a rule to auto-promote, allowing you to review the evidence behind the enforcement decision.

The best way to audit risky tool calls is checking action descriptions against active prevention rules before execution. This governance workflow validates proposed calls, determines if a block applies, and explains the originating failure pattern behind the restriction.

You need the prevention_rules MCP tool to list active rules, check action matches, and inspect feedback events. It provides the required governance interface to validate proposed agent tool calls against the enforced compliance rule set.

Agents repeat non-compliant actions when failure patterns have not been converted into actionable prevention rules. Generating rules from recurring feedback events ensures the system validates proposed tool calls and blocks matching risky behaviors before execution.