Skill: Set Up Monitoring

SkillMonitoring & ops

Workflow for implementing comprehensive monitoring and alerting. Use when the user needs to set up or improve service monitoring.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Skill: Set Up Monitoring skill

What this skill tells your AI

The instructions your AI receives, as published by girijashankarj/cursor-handbook in .cursor/skills/devops/monitoring/SKILL.md and read by ahel’s review.

Trigger

When the user needs to set up or improve service monitoring.

Steps

Step 1: Define Metrics

  • Request rate (throughput)
  • Error rate (4xx, 5xx)
  • Latency (p50, p95, p99)
  • Resource utilization (CPU, memory, disk)
  • Business metrics (domain-specific)

Step 2: Implement Structured Logging

  • JSON format for all logs
  • Required fields: timestamp, level, correlationId, service
  • No PII in logs
  • Appropriate log levels (error, warn, info, debug)

Step 3: Set Up Tracing

  • Add OpenTelemetry or provider-specific SDK
  • Instrument HTTP requests
  • Instrument database queries
  • Instrument external service calls
  • Configure sampling rate

Step 4: Create Dashboards

  • Service health overview
  • Request rate and error rate
  • Latency percentiles
  • Resource utilization
  • Business KPIs

Step 5: Configure Alerts

  • Error rate > 1% → P3
  • Error rate > 5% → P1
  • p99 latency > 2s → P3
  • CPU > 80% → P3
  • Health check failure → P1
  • Set notification channels

Step 6: Create Runbooks

  • For each alert, write a runbook:
    • What the alert means
    • Investigation steps
    • Resolution steps
    • Escalation path

Completion

Monitoring, alerting, and runbooks are in place.

Signals

GitHub stars
30
Forks
3
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
monitoring-girijashankarj
Source
github.com/girijashankarj/cursor-handbook