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Observability and metrics for AI agents - track calls, errors, latency
--- name: agent-metrics description: Observability and metrics for AI agents - track calls, errors, latency --- # 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 ```powershell # Install Python dependency pip install psutil ``` ## Usage ### Option 1: PowerShell (recommended on Windows) ```powershell .\agent-metrics.ps1 -Action record -MetricType call -Label "api_openai" ``` ### Option 2: Python CLI (cross-platform) ```powershell python metrics.py record --type call --label "api_openai" ``` ### Record an Error ```powershell .\agent-metrics.ps1 -Action record -MetricType error -Label "api_error" -Details "Rate limit exceeded" ``` ### Record Latency ```powershell .\agent-metrics.ps1 -Action record -MetricType latency -Label "task_process" -Value 1500 ``` ### View Dashboard ```powershell .\agent-metrics.ps1 -Action dashboard ``` ### View Resource Usage (CPU, Memory, Disk) ```powershell .\agent-metrics.ps1 -Action resources ``` ### Export Metrics ```powershell .\agent-metrics.ps1 -Action export -Format json -Output metrics.json ``` ### Get Summary ```powershell .\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--- name: agent-metrics description: Observability and metrics for AI agents - track calls, errors, latency --- # 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 ```powershell # Install Python dependency pip install psutil ``` ## Usage ### Option 1: PowerShell (recommended on Windows) ```powershell .\agent-metrics.ps1 -Action record -MetricType call -Label "api_openai" ``` ### Option 2: Python CLI (cross-platform) ```powershell python metrics.py record --type call --label "api_openai" ``` ### Record an Error ```powershell .\agent-metrics.ps1 -Action record -MetricType error -Label "api_error" -Details "Rate limit exceeded" ``` ### Record Latency ```powershell .\agent-metrics.ps1 -Action record -MetricType latency -Label "task_process" -Value 1500 ``` ### View Dashboard ```powershell .\agent-metrics.ps1 -Action dashboard ``` ### View Resource Usage (CPU, Memory, Disk) ```powershell .\agent-metrics.ps1 -Action resources ``` ### Export Metrics ```powershell .\agent-metrics.ps1 -Action export -Format json -Output metrics.json ``` ### Get Summary ```powershell .\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
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.