How do I install the Agent Metrics skill?

Run npx skillmds@latest add modbender/agent-metrics in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Agent Metrics skill do?

Observability and metrics for AI agents - track calls, errors, latency It is listed under AI & ML on SkillMD.

Is Agent Metrics safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Agent Metrics?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Agent Metrics free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Agent Metrics?

modbender (@modbender) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agent Metrics by modbender — Agent Skill

Name: Agent Metrics
Rating: 4.2 (5 reviews)
Author: modbender

File contents

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

---name: agent-metricsdescription: 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

Frequently asked questions

Agent Metrics