agent-governance

To add policy-based access controls to your AI agent, you can define governance policies that specify allowed tools, blocked patterns, rate limits, and human approval requirements using this Skill's governance patterns.

Semantic intent classification for AI agent safety is a mechanism that detects dangerous intent in user prompts before they reach the agent, ensuring compliance and reducing risks by preventing malicious or harmful commands from executing.

Yes, AI agent governance works with CrewAI and LangChain, as well as PydanticAI, OpenAI Agents, and AutoGen, providing tool-level governance decorators and trust scoring across these agent frameworks.

You implement trust scoring in AI agent frameworks by tracking agent reliability over time using decay-based trust scores, applying governance levels like Open, Standard, Strict, or Locked to match your specific safety requirements.

The best way to enforce compliance and safety in an AutoGen agent is to follow fail-closed policies, apply tool-level governance decorators, and maintain audit trails alongside semantic intent classification for comprehensive risk reduction.

You should use strict governance levels for AI agents when operating in high-risk environments requiring human approval, leveraging blocked patterns and rate limits to ensure compliance and prevent unauthorized actions.