agent-governance

To enforce policy on AI agents, define a GovernancePolicy with allowed tools, blocked patterns, and rate limits. Apply it to tool functions using a govern decorator, which intercepts actions and blocks unsafe prompts before execution.

Yes, you can add an audit trail to AI agent tools using built-in wrappers. The governance mechanism logs all tool usage interactions in an append-only format, providing a robust record for compliance verification and debugging.

Yes, this skill provides framework integration scaffolding for CrewAI and LangChain, alongside PydanticAI, OpenAI Agents SDK, and AutoGen. These adapters wire governance policies directly into existing agent architectures.

The best way to manage multi-agent trust scores is using the built-in governance model. It calculates and maintains trust metrics across multi-agent interactions, supporting ongoing risk management and accountability.

To require human approval for tool usage, configure your GovernancePolicy to include human approval rules. The govern decorator then enforces these rules, pausing execution to request manual authorization for specified actions.

To prevent unsafe actions in multi-agent coordination, apply governance policies that enforce intent classification and tool control. This restricts unauthorized actions and maintains a robust audit trail across all agent interactions.