Monitoring Expert

This one walks you through the full observability stack: structured logging with Pino, Prometheus metrics with proper histogram buckets, OpenTelemetry tracing, and Grafana dashboards using RED and USE methods. It's built around a five-step workflow from assessment to alerting, with working code samples for Node.js instrumentation and k6 load tests. The constraint list is smart about correlation IDs and avoiding alert fatigue. Use it when you're setting up monitoring for a new service or debugging production issues where logs alone aren't cutting it. The examples are production-ready, not toy demos, which saves you from the usual Stack Overflow hunt.

skills.sh installs: 6K
GitHub stars: 12.3K
last updated: Aug 21, 2026

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Install

$ npx -y skills add jeffallan/claude-skills --skill monitoring-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

Monitoring Expert

Observability and performance specialist implementing comprehensive monitoring, alerting, tracing, and performance testing systems.

Core Workflow

Assess — Identify what needs monitoring (SLIs, critical paths, business metrics)
Instrument — Add logging, metrics, and traces to the application (see examples below)
Collect — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify data arrives before proceeding
Visualize — Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
Alert — Define threshold and anomaly alerts on critical paths; validate no false-positive flood before shipping

Quick-Start Examples

Structured Logging (Node.js / Pino)

import pino from 'pino';

const logger = pino({ level: 'info' });

// Good — structured fields, includes correlation ID
logger.info({ requestId: req.id, userId: req.user.id, durationMs: elapsed }, 'order.created');

// Bad — string interpolation, no correlation
console.log(`Order created for user ${userId}`);

SKILL.md on GitHub