A robust management toolkit for monitoring, diagnosing, and optimizing OpenClaw AI agents through a professional DevOps workflow.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agentops
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agentops using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is AgentOps?
AgentOps is a professional-grade operations suite designed to provide deep visibility into the performance and stability of AI agents. As a key entry among Openclaw Skills, it bridges the gap between development and production by offering tools for health monitoring, session tracking, and resource optimization. The toolkit is tightly integrated with the OpenClaw ecosystem, ensuring that developers can maintain high availability and peak performance for their automated agents.
By utilizing a freemium model, AgentOps empowers users to start with essential diagnostic tools like log analyzers and health checks before scaling up to advanced automated alerting and multi-agent coordination. It is an indispensable asset for anyone looking to industrialize their Openclaw Skills and ensure reliable long-term operations.
AgentOps Use Cases
- Monitoring the real-time health and session status of active AI agents.
- Analyzing system logs to identify errors, warnings, or unexpected behavior in Openclaw Skills.
- Optimizing configuration files for better performance and resource management.
- Setting up automated alerts for CPU and memory usage thresholds.
- Diagnosing root causes for session timeouts or high memory consumption in complex agent environments.
How AgentOps Works
- The user triggers the tool via the command line or by mentioning specific operational keywords like health check or log analysis.
- AgentOps executes specialized Python scripts that interface directly with the OpenClaw service and session metadata.
- For basic maintenance, the tool parses OpenClaw logs and system metrics to provide a snapshot of current performance.
- For premium workflows, the tool uses logic-based diagnostic engines to perform root cause analysis on session failures.
- Results are outputted as actionable CLI text, structured JSON for further automation, or Markdown reports to assist in the lifecycle management of Openclaw Skills.
AgentOps Setup
To deploy this tool within your Openclaw Skills environment, ensure you have Python 3.8 or higher installed.
# Navigate to your agentops directory
cd agentops
# Run a comprehensive health check to verify your setup
python3 scripts/health_check.py --check all
# Monitor real-time performance
python3 scripts/perf_monitor.py --watch 30
AgentOps Data Schema & Taxonomy
AgentOps organizes operational data into structured formats to facilitate seamless integration with other Openclaw Skills.
| Data Type | Source | Description |
|---|---|---|
| Health Metrics | OpenClaw Service | Status of services, sessions, and configuration validity. |
| Log Data | ~/.openclaw/logs | Extracted errors, warnings, and anomaly patterns. |
| Performance Stats | System Resources | CPU, memory, and agent response time benchmarks. |
| Topology Map | Multi-Agent Logic | Dependency and conflict analysis between different agents. |
AgentOps Advanced Features
- Multi-agent coordination to analyze dependencies and topology between different Openclaw Skills.
- Automated alert management with configurable thresholds for system metrics and metric operators.
- Root cause diagnostic engine for rapid troubleshooting of session timeouts and high memory usage.
- Comprehensive performance reporting over custom time periods (e.g., 7-day reports) exported as Markdown.
- Advanced configuration optimizer that provides actionable improvement suggestions based on actual resource usage.
SKILL.md
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