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investigate-alert

Skill2 starsChanged 19 days agoApache-2.0View on GitHub

Quick triage of firing Prometheus alerts. Gets alerts, pod health, events, Kibana logs, known patterns. Escalates to debug_prod for serious issues. Use when user says "what's firing?", "check alerts", "any alerts?", or "investigate alert".

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    NEVER copy kubeconfig files: Use the correct file per environment:

    line 12
  2. Very specific:

    Use --kubeconfig=~/.kube/config.s or config.p with kubectl/oc.

    line 19
  3. Very specific:

    If auto_escalate and production: skill_run("debug_prod", ...)

    line 84
  4. Very specific:

    Update state/environments with status

    line 90

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Investigate Alert

Quick investigation of a firing Prometheus alert. For deep investigation, use debug_prod directly.

Kubeconfig Rules

NEVER copy kubeconfig files. Use the correct file per environment:

FileEnvironment
~/.kube/config.sStage
~/.kube/config.pProduction

Use --kubeconfig=~/.kube/config.s or config.p with kubectl/oc.

Inputs

InputTypeDefaultPurpose
environmentstringrequiredstage, production, or prod
namespacestringmainmain or billing
alert_namestring-Specific alert to investigate
auto_escalatebooltrueAuto-run debug_prod if critical

Persona

Load incident persona (prometheus, alertmanager, kibana, k8s tools).

Workflow

1. Bootstrap

  • persona_load("incident")
  • check_known_issues("prometheus_query")
  • check_known_issues("kubectl_get_pods")

2. Resolve Namespace

From config.json → namespaces:

  • Stage → tower-analytics-stage
  • Prod main → tower-analytics-prod
  • Prod billing → tower-analytics-prod-billing

3. Get Alerts

  • prometheus_alerts(environment, namespace, state="firing")
  • Parse severity (critical, high, low)

4. Quick Health Check

  • k8s_namespace_health(namespace, environment) or kubectl_get_pods(namespace, environment)
  • kubectl_top_pods(namespace, environment) — CPU/memory usage
  • kubectl_get_events(namespace, environment, field_selector="type=Warning")
  • prometheus_query_range — error rate trend over last hour

5. Search Logs

  • kibana_search_logs(query="error OR exception OR critical", namespace, environment, limit=10)
  • kibana_get_errors(namespace, environment)

6. Check Known Patterns

  • memory_read("learned/patterns") — match alerts/pod issues against error_patterns

7. Knowledge & Code Search

  • code_search(query=alert_name, project="automation-analytics-backend", limit=5)
  • knowledge_query(project="automation-analytics-backend", persona="devops", section="gotchas")

8. Check Existing Silences

  • alertmanager_silences(environment)
  • alertmanager_receivers(environment)

9. Assess Severity

  • Critical/high + unhealthy pods → needs_escalation
  • If auto_escalate and production: skill_run("debug_prod", ...)

10. Notify & Log

  • If critical: skill_run("notify_team", template="alert", ...)
  • memory_session_log("Investigated alerts", ...)
  • Update state/environments with status

11. Failure Recovery

  • "connection refused" → vpn_connect()
  • "unauthorized" on k8s → kube_login(cluster="stage"|"prod")
  • Kibana 401 → open Kibana in browser first
  • learn_tool_fix(...) for recurring patterns

Output

Report with: alerts count, pod health, resource usage, events, Kibana errors, pattern matches, silence recommendation, escalation status.

Chains To

  • debug_prod — deep investigation
  • silence_alert — if known issue
  • create_jira_issue — track alert
  • rollout_restart, scale_deployment — remediation

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