clawguard-guardian

Monitor AI agent behavior and enforce safe actions at runtime.

50|4|Updated Mar 15, 2026
One-click install
npx skills add https://github.com/SafeAgent-Beihang/clawguard --skill clawguard-guardian
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: clawguard-guardian
Source: https://github.com/SafeAgent-Beihang/clawguard/tree/main/guardian-skill
Command: npx skills add https://github.com/SafeAgent-Beihang/clawguard --skill clawguard-guardian

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

ClawGuard Guardian provides real-time behavior monitoring and emergency response to AI agents, preventing dangerous actions and enabling rapid containment.

Core Features & Use Cases

  • Real-time monitoring of commands, file access, network activity, and prompt injections.
  • Auto-freeze, session replay, and evidence-preserving responses for incident handling.
  • Risk-based decisioning with audit logging and integration hooks for Guardian to coordinate with Detect and Auditor.

Quick Start

Start Guardian monitoring by running the Guardian CLI and saying Start guardian to begin protection.

Frequently Asked Questions about clawguard-guardian

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor AI agent behavior at runtime to prevent dangerous actions?

Runtime monitoring tracks AI agent commands, file access, network activity, and prompt injections in real time. It intercepts risks and automatically enforces safe, compliant actions to prevent dangerous operations during execution.

What is session replay for incident response and how does it work?

Session replay preserves agent activity evidence during incident handling. When a risk is detected, it freezes the session and records the full behavioral context, enabling rapid containment and post-incident analysis.

How do I start runtime protection for my AI agents?

Start runtime protection by running the Guardian CLI and issuing the command to begin monitoring. This activates real-time behavior tracking, risk scoring, and automatic interception of unsafe commands immediately.

Can I integrate runtime monitoring with existing audit logging systems?

Yes, runtime monitoring includes integration hooks designed to coordinate with Auditor and Detect components. It generates audit logs and risk-based decisions that feed directly into coordinated protective responses across your guardianship contexts.

What are the limitations of risk-based interception for AI agent safety?

Risk-based interception focuses on runtime command monitoring and session freezing. It requires active guardianship contexts to function and does not prevent vulnerabilities in static code or model training data prior to execution.