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Jeffallan/claude-skills/skills/monitoring-expert/SKILL.md

monitoring-expert

Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments distributed tracing. Implements Prometheus/Grafana stacks, conducts load testing, performs application profiling, and plans infrastructure capacity. Use when setting up application monitoring, adding observability to services, debugging production issues with logs/metrics/traces, running load tests with k6 or Artillery, profiling CPU/memory bottle

Source repository stars
10,762
Declared platforms
0
Static risk flags
1
Last source update
2026-05-20
Source checked
2026-07-28

Decision brief

What it does—and where it fits

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

Best for

  • Use when setting up application monitoring, adding observability to services, debugging production issues with logs/metrics/traces, running load tests with k6 or Artillery, profiling CPU/memory bottle

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/Jeffallan/claude-skills --skill "skills/monitoring-expert"
Safe inspection promptEditorial

Inspect the Agent Skill "monitoring-expert" from https://github.com/Jeffallan/claude-skills/blob/e8be415bc94d8d6ebddc2fb50e5d03c6e27d4319/skills/monitoring-expert/SKILL.md at commit e8be415bc94d8d6ebddc2fb50e5d03c6e27d4319. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Core Workflow

    1. Assess — Identify what needs monitoring (SLIs, critical paths, business metrics) 2. Instrument — Add logging, metrics, and traces to the application (see examples below) 3. Collect — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify dat…

    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
  2. 02

    Quick-Start Examples

    Review the “Quick-Start Examples” section in the pinned source before continuing.

    Review and apply the “Quick-Start Examples” source section.
  3. 03

    Structured Logging (Node.js / Pino)

    Review the “Structured Logging (Node.js / Pino)” section in the pinned source before continuing.

    Review and apply the “Structured Logging (Node.js / Pino)” source section.
  4. 04

    Prometheus Metrics (Node.js)

    Review the “Prometheus Metrics (Node.js)” section in the pinned source before continuing.

    Review and apply the “Prometheus Metrics (Node.js)” source section.
  5. 05

    OpenTelemetry Tracing (Node.js)

    Review the “OpenTelemetry Tracing (Node.js)” section in the pinned source before continuing.

    Review and apply the “OpenTelemetry Tracing (Node.js)” source section.

Permission review

Static risk signals and limitations

Network access

medium · line 69

The documentation includes network, browsing, or remote request actions.

traceExporter: new OTLPTraceExporter({ url: 'http://jaeger:4318/v1/traces' }),

Network access

medium · line 126

The documentation includes network, browsing, or remote request actions.

const res = http.get('https://api.example.com/orders');

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score76/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars10,762SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
Jeffallan/claude-skills
Skill path
skills/monitoring-expert/SKILL.md
Commit
e8be415bc94d8d6ebddc2fb50e5d03c6e27d4319
License
MIT
Collected
2026-07-28
Default branch
main
View the original SKILL.md

Monitoring Expert

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

Core Workflow

  1. Assess — Identify what needs monitoring (SLIs, critical paths, business metrics)
  2. Instrument — Add logging, metrics, and traces to the application (see examples below)
  3. Collect — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify data arrives before proceeding
  4. Visualize — Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
  5. 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}`);

Prometheus Metrics (Node.js)

import { Counter, Histogram, register } from 'prom-client';

const httpRequests = new Counter({
  name: 'http_requests_total',
  help: 'Total HTTP requests',
  labelNames: ['method', 'route', 'status'],
});

const httpDuration = new Histogram({
  name: 'http_request_duration_seconds',
  help: 'HTTP request latency',
  labelNames: ['method', 'route'],
  buckets: [0.05, 0.1, 0.3, 0.5, 1, 2, 5],
});

// Instrument a route
app.use((req, res, next) => {
  const end = httpDuration.startTimer({ method: req.method, route: req.path });
  res.on('finish', () => {
    httpRequests.inc({ method: req.method, route: req.path, status: res.statusCode });
    end();
  });
  next();
});

// Expose scrape endpoint
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', register.contentType);
  res.end(await register.metrics());
});

OpenTelemetry Tracing (Node.js)

import { NodeSDK } from '@opentelemetry/sdk-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
import { trace } from '@opentelemetry/api';

const sdk = new NodeSDK({
  traceExporter: new OTLPTraceExporter({ url: 'http://jaeger:4318/v1/traces' }),
});
sdk.start();

// Manual span around a critical operation
const tracer = trace.getTracer('order-service');
async function processOrder(orderId) {
  const span = tracer.startSpan('order.process');
  span.setAttribute('order.id', orderId);
  try {
    const result = await db.saveOrder(orderId);
    span.setStatus({ code: SpanStatusCode.OK });
    return result;
  } catch (err) {
    span.recordException(err);
    span.setStatus({ code: SpanStatusCode.ERROR });
    throw err;
  } finally {
    span.end();
  }
}

Prometheus Alerting Rule

groups:
  - name: api.rules
    rules:
      - alert: HighErrorRate
        expr: |
          rate(http_requests_total{status=~"5.."}[5m])
          / rate(http_requests_total[5m]) > 0.05
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Error rate above 5% on {{ $labels.route }}"

k6 Load Test

import http from 'k6/http';
import { check, sleep } from 'k6';

export const options = {
  stages: [
    { duration: '1m', target: 50 },   // ramp up
    { duration: '5m', target: 50 },   // sustained load
    { duration: '1m', target: 0 },    // ramp down
  ],
  thresholds: {
    http_req_duration: ['p(95)<500'],  // 95th percentile < 500 ms
    http_req_failed:   ['rate<0.01'],  // error rate < 1%
  },
};

export default function () {
  const res = http.get('https://api.example.com/orders');
  check(res, { 'status is 200': (r) => r.status === 200 });
  sleep(1);
}

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Loggingreferences/structured-logging.mdPino, JSON logging
Metricsreferences/prometheus-metrics.mdCounter, Histogram, Gauge
Tracingreferences/opentelemetry.mdOpenTelemetry, spans
Alertingreferences/alerting-rules.mdPrometheus alerts
Dashboardsreferences/dashboards.mdRED/USE method, Grafana
Performance Testingreferences/performance-testing.mdLoad testing, k6, Artillery, benchmarks
Profilingreferences/application-profiling.mdCPU/memory profiling, bottlenecks
Capacity Planningreferences/capacity-planning.mdScaling, forecasting, budgets

Constraints

MUST DO

  • Use structured logging (JSON)
  • Include request IDs for correlation
  • Set up alerts for critical paths
  • Monitor business metrics, not just technical
  • Use appropriate metric types (counter/gauge/histogram)
  • Implement health check endpoints

MUST NOT DO

  • Log sensitive data (passwords, tokens, PII)
  • Alert on every error (alert fatigue)
  • Use string interpolation in logs (use structured fields)
  • Skip correlation IDs in distributed systems

Documentation

Alternatives

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