agent-governance

What This Skill Does

The agent-governance skill provides a robust framework for implementing safety, security, and policy-based controls within AI agent systems. It acts as a middleware layer between user intent and tool execution, allowing developers to define declarative policies that govern what an agent can and cannot do. By utilizing this skill, you can enforce tool allowlists, block dangerous content patterns, set operational rate limits, and mandate human-in-the-loop approvals for sensitive tasks like financial transactions or database deletions. This ensures that agents operate within strict organizational boundaries while maintaining a transparent audit trail of their decision-making processes.

Installation

To integrate this governance layer into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/boleyn/agent-governance

Use Cases

• Enterprise Compliance: Ensuring agents strictly follow internal data handling policies by blocking unauthorized API calls.
• Multi-Agent Orchestration: Establishing trust boundaries between a primary agent and its child agents, preventing privilege escalation.
• Production Guardrails: Implementing automated rate limiting and content filtering to prevent malicious prompt injection or accidental resource exhaustion.
• Audit-Ready Operations: Capturing every tool-use event into a centralized logging system to meet industry regulatory requirements.

Example Prompts

1. "Apply a governance policy to the research agent that blocks access to the file-system and requires human review for all external API calls."
2. "Check the current system configuration to see if there are any active blocked patterns that would prevent the agent from accessing the production database."
3. "Generate an audit report for all agent tool executions from the last 24 hours to ensure compliance with our security policy."

Tips & Limitations

• Policy Order Matters: When composing multiple policies, use 'most-restrictive-wins' logic to prevent gaps in security coverage.
• Performance Overhead: Frequent policy checking can add latency to agent responses; cache policy results where possible for static evaluations.
• Continuous Monitoring: Governance is not a 'set and forget' task. Regularly review your blocked patterns and human-approval requirements as agent capabilities evolve and threats change.
• Human Intervention: Always ensure that critical actions requiring human approval have a reliable notification path to prevent agents from becoming 'stuck' waiting for input.