Incident Runbook Templates

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/incident-runbook-templates

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

Incident Runbook Templates Production-ready templates for incident response runbooks covering detection, triage, mitigation, resolution, and communication.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core Concepts, Runbook Templates, Impact Assessment, Detection, Initial Triage (First 5 Minutes), Communication Templates.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• The task is unrelated to incident runbook templates
• You need a different domain or tool outside this scope
• Creating incident response procedures
• Building service-specific runbooks
• Establishing escalation paths
• Documenting recovery procedures

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Clarify goals, constraints, and required inputs.
2. Apply relevant best practices and validate outcomes.
3. Provide actionable steps and verification.
4. If detailed examples are required, open resources/implementation-playbook.md.
5. from:
6. ipBlock:
7. 192.168.1.0/24 # Suspicious range

Imported Workflow Notes

Imported: Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open

  resources/implementation-playbook.md

  .

Imported: Mitigation Procedures

4.1 Service Completely Down

# Step 1: Check pod status
kubectl get pods -n payments

# Step 2: If pods are crash-looping, check logs
kubectl logs -n payments -l app=payment-service --tail=100

# Step 3: Check recent deployments
kubectl rollout history deployment/payment-service -n payments

# Step 4: ROLLBACK if recent deploy is suspect
kubectl rollout undo deployment/payment-service -n payments

# Step 5: Scale up if resource constrained
kubectl scale deployment/payment-service -n payments --replicas=10

# Step 6: Verify recovery
kubectl rollout status deployment/payment-service -n payments

4.2 High Latency

# Step 1: Check database connections
kubectl exec -n payments deploy/payment-service -- \
  curl localhost:8080/metrics | grep db_pool

# Step 2: Check slow queries (if DB issue)
psql -h $DB_HOST -U $DB_USER -c "
  SELECT pid, now() - query_start AS duration, query
  FROM pg_stat_activity
  WHERE state = 'active' AND duration > interval '5 seconds'
  ORDER BY duration DESC;"

# Step 3: Kill long-running queries if needed
psql -h $DB_HOST -U $DB_USER -c "SELECT pg_terminate_backend(pid);"

# Step 4: Check external dependency latency
curl -w "@curl-format.txt" -o /dev/null -s https://api.stripe.com/v1/health

# Step 5: Enable circuit breaker if dependency is slow
kubectl set env deployment/payment-service \
  STRIPE_CIRCUIT_BREAKER_ENABLED=true -n payments

4.3 Partial Failures (Specific Errors)

# Step 1: Identify error pattern
kubectl logs -n payments -l app=payment-service --tail=500 | \
  grep -i error | sort | uniq -c | sort -rn | head -20

# Step 2: Check error tracking
# Go to Sentry: https://sentry.io/payments

# Step 3: If specific endpoint, enable feature flag to disable
curl -X POST https://api.company.com/internal/feature-flags \
  -d '{"flag": "DISABLE_PROBLEMATIC_FEATURE", "enabled": true}'

# Step 4: If data issue, check recent data changes
psql -h $DB_HOST -c "
  SELECT * FROM audit_log
  WHERE table_name = 'payment_methods'
  AND created_at > now() - interval '1 hour';"

4.4 Traffic Surge

# Step 1: Check current request rate
kubectl top pods -n payments

# Step 2: Scale horizontally
kubectl scale deployment/payment-service -n payments --replicas=20

# Step 3: Enable rate limiting
kubectl set env deployment/payment-service \
  RATE_LIMIT_ENABLED=true \
  RATE_LIMIT_RPS=1000 -n payments

# Step 4: If attack, block suspicious IPs
kubectl apply -f - <<EOF
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: block-suspicious
  namespace: payments
spec:
  podSelector:
    matchLabels:
      app: payment-service
  ingress:
  - from:
    - ipBlock:
        cidr: 0.0.0.0/0
        except:
        - 192.168.1.0/24  # Suspicious range
EOF

Imported: Verification Steps

# Verify service is healthy
curl -s https://api.company.com/payments/health | jq

# Verify error rate is back to normal
curl -s "http://prometheus:9090/api/v1/query?query=sum(rate(http_requests_total{status=~'5..'}[5m]))" | jq '.data.result[0].value[1]'

# Verify latency is acceptable
curl -s "http://prometheus:9090/api/v1/query?query=histogram_quantile(0.99,sum(rate(http_request_duration_seconds_bucket[5m]))by(le))" | jq

# Smoke test critical flows
./scripts/smoke-test-payments.sh

Imported: Rollback Procedures

# Rollback Kubernetes deployment
kubectl rollout undo deployment/payment-service -n payments

# Rollback database migration (if applicable)
./scripts/db-rollback.sh $MIGRATION_VERSION

# Rollback feature flag
curl -X POST https://api.company.com/internal/feature-flags \
  -d '{"flag": "NEW_PAYMENT_FLOW", "enabled": false}'

Imported: Overview

Service: Payment Processing Service Owner: Platform Team Slack: #payments-incidents PagerDuty: payments-oncall

Imported: Core Concepts

1. Incident Severity Levels

2. Runbook Structure

1. Overview & Impact
2. Detection & Alerts
3. Initial Triage
4. Mitigation Steps
5. Root Cause Investigation
6. Resolution Procedures
7. Verification & Rollback
8. Communication Templates
9. Escalation Matrix

Examples

Example 1: Ask for the upstream workflow directly

Use @incident-runbook-templates to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @incident-runbook-templates against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @incident-runbook-templates for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @incident-runbook-templates using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep runbooks updated - Review after every incident
• Test runbooks regularly - Game days, chaos engineering
• Include rollback steps - Always have an escape hatch
• Document assumptions - What must be true for steps to work
• Link to dashboards - Quick access during stress
• Don't assume knowledge - Write for 3 AM brain
• Don't skip verification - Confirm each step worked

Imported Operating Notes

Imported: Best Practices

Do's

• Keep runbooks updated - Review after every incident
• Test runbooks regularly - Game days, chaos engineering
• Include rollback steps - Always have an escape hatch
• Document assumptions - What must be true for steps to work
• Link to dashboards - Quick access during stress

Don'ts

• Don't assume knowledge - Write for 3 AM brain
• Don't skip verification - Confirm each step worked
• Don't forget communication - Keep stakeholders informed
• Don't work alone - Escalate early
• Don't skip postmortems - Learn from every incident

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/incident-runbook-templates

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @base

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @calc

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @draw

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @image-studio

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Escalation Matrix

Imported: Quick Reference

SELECT count(*) FROM pg_stat_activity;

SELECT pg_terminate_backend(pid);

SELECT extract(epoch from (now() - pg_last_xact_replay_timestamp()));

SELECT * FROM pg_locks WHERE NOT granted;

Imported: Resources

• Google SRE Book - Incident Management
• PagerDuty Incident Response
• Atlassian Incident Management

Imported: Runbook Templates

Template 1: Service Outage Runbook

# [Service Name] Outage Runbook

#### Imported: Impact Assessment

- [ ] Which customers are affected?
- [ ] What percentage of traffic is impacted?
- [ ] Are there financial implications?
- [ ] What's the blast radius?

#### Imported: Detection

### Alerts
- `payment_error_rate > 5%` (PagerDuty)
- `payment_latency_p99 > 2s` (Slack)
- `payment_success_rate < 95%` (PagerDuty)

### Dashboards
- [Payment Service Dashboard](https://grafana/d/payments)
- [Error Tracking](https://sentry.io/payments)
- [Dependency Status](https://status.stripe.com)

#### Imported: Initial Triage (First 5 Minutes)

### 1. Assess Scope
```bash
# Check service health
kubectl get pods -n payments -l app=payment-service

# Check recent deployments
kubectl rollout history deployment/payment-service -n payments

# Check error rates
curl -s "http://prometheus:9090/api/v1/query?query=sum(rate(http_requests_total{status=~'5..'}[5m]))"

2. Quick Health Checks

• Can you reach the service?

  curl -I https://api.company.com/payments/health

• Database connectivity? Check connection pool metrics
• External dependencies? Check Stripe, bank API status
• Recent changes? Check deploy history

3. Initial Classification

Imported: Communication Templates

Initial Notification (Internal)

🚨 INCIDENT: Payment Service Degradation

Severity: SEV2
Status: Investigating
Impact: ~20% of payment requests failing
Start Time: [TIME]
Incident Commander: [NAME]

Current Actions:
- Investigating root cause
- Scaling up service
- Monitoring dashboards

Updates in #payments-incidents

Status Update

📊 UPDATE: Payment Service Incident

Status: Mitigating
Impact: Reduced to ~5% failure rate
Duration: 25 minutes

Actions Taken:
- Rolled back deployment v2.3.4 → v2.3.3
- Scaled service from 5 → 10 replicas

Next Steps:
- Continuing to monitor
- Root cause analysis in progress

ETA to Resolution: ~15 minutes

Resolution Notification

✅ RESOLVED: Payment Service Incident

Duration: 45 minutes
Impact: ~5,000 affected transactions
Root Cause: Memory leak in v2.3.4

Resolution:
- Rolled back to v2.3.3
- Transactions auto-retried successfully

Follow-up:
- Postmortem scheduled for [DATE]
- Bug fix in progress

### Template 2: Database Incident Runbook

```markdown
# Database Incident Runbook

#### Imported: Connection Pool Exhaustion

```sql
-- Check current connections
SELECT datname, usename, state, count(*)
FROM pg_stat_activity
GROUP BY datname, usename, state
ORDER BY count(*) DESC;

-- Identify long-running connections
SELECT pid, usename, datname, state, query_start, query
FROM pg_stat_activity
WHERE state != 'idle'
ORDER BY query_start;

-- Terminate idle connections
SELECT pg_terminate_backend(pid)
FROM pg_stat_activity
WHERE state = 'idle'
AND query_start < now() - interval '10 minutes';

Imported: Replication Lag

-- Check lag on replica
SELECT
  CASE
    WHEN pg_last_wal_receive_lsn() = pg_last_wal_replay_lsn() THEN 0
    ELSE extract(epoch from now() - pg_last_xact_replay_timestamp())
  END AS lag_seconds;

-- If lag > 60s, consider:
-- 1. Check network between primary/replica
-- 2. Check replica disk I/O
-- 3. Consider failover if unrecoverable

Imported: Disk Space Critical

# Check disk usage
df -h /var/lib/postgresql/data

# Find large tables
psql -c "SELECT relname, pg_size_pretty(pg_total_relation_size(relid))
FROM pg_catalog.pg_statio_user_tables
ORDER BY pg_total_relation_size(relid) DESC
LIMIT 10;"

# VACUUM to reclaim space
psql -c "VACUUM FULL large_table;"

# If emergency, delete old data or expand disk

#### Imported: Limitations

- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.