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Monitor

Skill KhaiTrang1995/agentic-awesome-kits/kits/devops/k8s-kit/.claude/skills/monitor

A universal collection of reusable Loop Engineering kits for AI coding agents—not just prompts. Each kit combines Skills, Rules, Templates, workflows, and validation loops to help agents autonomously plan, execute, verify, fix, and improve engineering tasks.

Install
npx -y skills add KhaiTrang1995/agentic-awesome-kits --skill monitor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

3 things to look at

  • 22 days oldThe repository was created 22 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Generate monitoring config — Prometheus alert rules, Grafana dashboard JSON, ServiceMonitor.

SKILL.md

1.0 KB, as published. Nobody here has run it

/monitor — Generate Monitoring Config

Input examples

/monitor container-api --alerts --dashboard
/monitor container-api --slo 99.9
/monitor --alerts entire namespace prod

Output

monitoring/
  {app}/
    prometheus-rules.yaml       ← Alert rules
    servicemonitor.yaml         ← Scrape config
    grafana-dashboard.json      ← Dashboard

Sample alert rules

  • HighErrorRate: error rate > 1% over 5 minutes
  • HighLatency: p99 > 1s over 5 minutes
  • PodCrashLoop: restarts > 3 times in 10 minutes
  • HighMemory: memory > 90% of limit
  • HighCPU: CPU > 80% of limit sustained for 10 minutes

Dashboard panels

  • Request rate (req/s)
  • Error rate (%)
  • Latency percentiles (p50, p95, p99)
  • CPU / Memory usage
  • Pod count (ready vs desired)

References

  • @.claude/rules/k8s-conventions.md

Gives 0 of the 12 instructions most monitoring observability skills give

Counted across 481 of the 483 authors here whose files we hold, read 2026-08-06

  • link every alert to a runbookin 43 of 481, across 35 files
  • use structured json loggingin 36 of 481, across 31 files
  • alert on user-facing symptomsin 20 of 481, across 15 files
  • emit structured JSON logs with stable event namesin 18 of 481, across 13 files
  • propagate trace context across boundariesin 16 of 481
  • use histograms for latency trackingin 14 of 481, across 9 files
  • use OpenTelemetry for distributed tracingin 13 of 481, across 8 files
  • include a correlation ID on every log linein 13 of 481, across 8 files
  • Define service level objectivesin 10 of 481, across 7 files
  • Call useAzureMonitor before importing other modulesin 9 of 481, across 2 files
  • stop and ask for clarification if inputs are missingin 9 of 481, across 2 files
  • define on-call questions before adding telemetryin 9 of 481, across 4 files

Said here and by no other author read

  • Generate ServiceMonitor scrape config.
  • Write monitoring files to a monitoring directory.

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.