Skill: Set Up Monitoring
SkillMonitoring & opsWorkflow 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.
No other account needed.
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