ClawHub

Agent Safety Monitor

Real-time AI agent safety monitoring, anomaly detection, and constraint enforcement. Use when building agent guardrails, detecting unsafe behaviors, enforcing action limits, or creating safety dashboards for autonomous AI systems. Covers behavior logging, rule engines, alert systems, and compliance tracking.

Audits

Pending
ClawScanReview

Agentic behavior and permission review.

Static analysisPass

Pattern checks against bundled files.

VirusTotalPending

Multi-engine malware detections and file reputation.

Install

openclaw skills install agent-safety-monitor

Agent Safety Monitor

Monitor AI agent behavior in real-time, detect anomalies, and enforce safety constraints.

Quick Start

Run the monitor against an agent log stream:

python3 scripts/monitor.py --config safety_rules.yaml --input agent_logs/

Architecture

Agent Actions → Event Stream → Rule Engine → Alerts → Dashboard
                                   ↓
                              Anomaly Detector
                                   ↓
                              Auto-Pause/Kill

Safety Rule Types

  1. Rate limits: Max N actions per minute/hour
  2. Action allowlists: Only permit specific tool calls
  3. Content filters: Block PII exfiltration, harmful outputs
  4. Budget caps: Stop when cost exceeds threshold
  5. Scope limits: Restrict file/API/network access
  6. Behavioral anomalies: Flag unusual patterns (tool call frequency spikes, repetitive loops)

Rule Configuration

See references/rules-reference.md for the YAML schema.

Alert Channels

  • Console (default)
  • Webhook (Slack, Discord)
  • File log
  • Dashboard (HTTP server)

Dashboard

Launch the monitoring dashboard:

python3 scripts/dashboard.py --port 8080