dvcrn Agent Metrics Skill
Track and monitor your AI agent's behavior with built-in observability.
Files included:
metrics.py- Python CLI (cross-platform)agent-metrics.ps1- PowerShell wrapper (Windows)
What it does
- Call Tracking - Count API calls, messages, tasks
- Error Logging - Track errors with stack traces
- Latency Metrics - Measure response times
- Resource Usage - CPU, memory, network
- Simple Dashboard - Terminal-based metrics view
- Export - JSON export for external dashboards
Installation
# Install Python dependency
pip install psutil
Usage
Option 1: PowerShell (recommended on Windows)
.\agent-metrics.ps1 -Action record -MetricType call -Label "api_openai"
Option 2: Python CLI (cross-platform)
python metrics.py record --type call --label "api_openai"
Record an Error
.\agent-metrics.ps1 -Action record -MetricType error -Label "api_error" -Details "Rate limit exceeded"
Record Latency
.\agent-metrics.ps1 -Action record -MetricType latency -Label "task_process" -Value 1500
View Dashboard
.\agent-metrics.ps1 -Action dashboard
View Resource Usage (CPU, Memory, Disk)
.\agent-metrics.ps1 -Action resources
Export Metrics
.\agent-metrics.ps1 -Action export -Format json -Output metrics.json
Get Summary
.\agent-metrics.ps1 -Action summary
Metrics Types
| Type | Description | Fields |
|---|---|---|
| call | API call made | label, timestamp |
| error | Error occurred | label, details, timestamp |
| latency | Response time (ms) | label, value, timestamp |
| custom | Custom metric | label, value |
Dashboard Example
╔═══════════════════════════════════════════════╗
║ AGENT METRICS DASHBOARD ║
╠═══════════════════════════════════════════════╣
║ Total Calls: 1,247 ║
║ Total Errors: 23 ║
║ Error Rate: 1.84% ║
║ Avg Latency: 234ms ║
║ Uptime: 4h 32m ║
╠═══════════════════════════════════════════════╣
║ Top Labels: ║
║ api_openai 892 (71.5%) ║
║ api_claude 234 (18.8%) ║
║ task_process 121 (9.7%) ║
╚═══════════════════════════════════════════════╝
Requirements
- Python 3.8+
- psutil library
License
MIT