Ai Monitoring
Helps with AI, monitoring as part of automating DevOps pipelines and CI/CD workflows workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add ai-monitoring npx -- -y @trustedskills/ai-monitoring
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"ai-monitoring": {
"command": "npx",
"args": [
"-y",
"@trustedskills/ai-monitoring"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The ai-monitoring skill allows an AI agent to track and report on the performance of other AI agents or systems. It can collect metrics like response time, error rates, and resource utilization. This enables proactive identification of issues and optimization opportunities within AI workflows.
When to use it
- Debugging slow responses: Identify bottlenecks in a chain of AI tools by monitoring their individual execution times.
- Detecting errors: Track error rates from specific AI agents to pinpoint failing components.
- Resource Optimization: Monitor resource usage (e.g., API calls, memory) to identify areas for cost savings or efficiency improvements.
- Performance Baseline: Establish a baseline of performance metrics to measure the impact of changes and updates.
Key capabilities
- Metric collection
- Error rate tracking
- Response time measurement
- Resource utilization monitoring
Example prompts
- "Monitor the response time of the summarization agent."
- "Track error rates for the translation tool over the last hour."
- "Report on API call usage by the code generation agent."
Tips & gotchas
The skill requires access to logs or metrics from the AI agents being monitored. Ensure appropriate permissions and logging are configured before deployment.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.