alerting-oncall
alerting-oncall is an engineering AI skill with a core value of Set up alerting rules, configure on-call rotations, and manage incident response workflows. It
helps developers solve real-world problems in the engineering domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Set up alerting rules, configure on-call rotations, and manage incident response workflows.
Quick Facts
mkdir -p ./skills/alerting-oncall && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/alerting-oncall/SKILL.md -o ./skills/alerting-oncall/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Alerting & On-Call
Configure effective alerting and on-call management for production systems.
Prerequisites
- Monitoring system (Prometheus, Datadog, etc.)
- On-call platform (PagerDuty, Opsgenie, Grafana OnCall)
- Communication channels (Slack, email)
Alerting Best Practices
Alert Categories
# Severity levels
critical:
- Service completely down
- Data loss imminent
- Security breach
response: Immediate page, wake people up
high:
- Service degraded significantly
- Error rate above SLO
- Capacity near limit
response: Page during business hours, notify after hours
medium:
- Performance degradation
- Non-critical component failure
- Warning thresholds exceeded
response: Notify via Slack, review next business day
low:
- Informational alerts
- Capacity planning triggers
- Routine maintenance needed
response: Email notification, weekly reviewAlert Design Principles
# Good alert characteristics
alerts:
actionable:
- Every alert should require human action
- Include runbook links
- Clear remediation steps
relevant:
- Alert on symptoms, not causes
- Focus on user impact
- Avoid alerting on expected behavior
timely:
- Appropriate thresholds
- Suitable evaluation windows
- Account for normal variance
unique:
- No duplicate alerts
- Proper alert grouping
- Clear ownershipPrometheus Alerting
Alert Rules
# prometheus/rules/alerts.yml
groups:
- name: service_alerts
rules:
# High-level service health
- alert: ServiceDown
expr: up{job="myapp"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Service {{ $labels.instance }} is down"
description: "{{ $labels.job }} on {{ $labels.instance }} has been down for more than 1 minute."
runbook_url: "https://wiki.example.com/runbooks/service-down"
# Error rate alert
- alert: HighErrorRate
expr: |
sum(rate(http_requests_total{status=~"5.."}[5m])) by (service)
/ sum(rate(http_requests_total[5m])) by (service) > 0.05
for: 5m
labels:
severity: critical
annotations:
summary: "High error rate for {{ $labels.service }}"
description: "Error rate is {{ $value | humanizePercentage }} for the last 5 minutes"
# Latency alert (SLO-based)
- alert: HighLatency
expr: |
histogram_quantile(0.95,
sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service)
) > 0.5
for: 5m
labels:
severity: high
annotations:
summary: "P95 latency above 500ms for {{ $labels.service }}"Alertmanager Configuration
# alertmanager.yml
global:
resolve_timeout: 5m
slack_api_url: 'https://hooks.slack.com/services/xxx'
pagerduty_url: 'https://events.pagerduty.com/v2/enqueue'
templates:
- '/etc/alertmanager/templates/*.tmpl'
route:
receiver: 'default-receiver'
group_by: ['alertname', 'service']
group_wait: 30s
group_interval: 5m
repeat_interval: 4h
routes:
# Critical alerts go to PagerDuty
- match:
severity: critical
receiver: 'pagerduty-critical'
group_wait: 0s
repeat_interval: 1h
# High severity during business hours
- match:
severity: high
receiver: 'slack-high'
active_time_intervals:
- business-hours
# Route by team
- match_re:
team: platform.*
receiver: 'platform-team'
receivers:
- name: 'default-receiver'
slack_configs:
- channel: '#alerts'
send_resolved: true
- name: 'pagerduty-critical'
pagerduty_configs:
- service_key: 'xxx'
severity: critical
description: '{{ .CommonAnnotations.summary }}'
details:
firing: '{{ template "pagerduty.firing" . }}'
- name: 'slack-high'
slack_con🎯 Best For
- Claude users
- AI users
💡 Use Cases
- Using alerting-oncall in daily workflow
- Automating repetitive engineering tasks
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply alerting-oncall to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
How do I install alerting-oncall?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/alerting-oncall/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Not reading the full skill
Skills contain important context and edge cases beyond the quick start.