Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add latestaiagents/agent-skills --skill kubernetes-troubleshootinggit clone --depth 1 https://github.com/latestaiagents/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/latestaiagents/agent-skills/kubernetes-troubleshooting)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/kubernetes-troubleshooting"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/kubernetes-troubleshooting/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/kubernetes-troubleshooting"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/kubernetes-troubleshooting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00084 | $0.01804 |
| Opus 5 | $0.00042 | $0.00902 |
| Sonnet 5 | $0.00017 | $0.00361 |
| Haiku 4.5 | $0.00008 | $0.00180 |
Grade A, and why
kubernetes-troubleshooting scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
kubectl run test --rm -it --image=busybox -- wget -qO- <service>:<port> How it starts
The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kubernetes Troubleshooting
Systematic approaches to diagnose and fix common Kubernetes issues.
Troubleshooting Framework
1. What's the symptom? (pod not starting, service unreachable, etc.)
2. Where's the problem? (pod, service, ingress, node, cluster)
3. What do the events say?
4. What do the logs say?
5. What changed recently?
Pod Issues
Pod Status Quick Reference
| Status | Meaning | First Check |
|---|---|---|
| Pending | Can't be scheduled | kubectl describe pod |
| ContainerCreating | Image pulling or volume mounting | Events, kubectl get events |
| CrashLoopBackOff | Container crashes repeatedly | kubectl logs --previous |
| ImagePullBackOff | Can't pull container image | Image name, credentials |
| Error | Container exited with error | kubectl logs |
| OOMKilled | Out of memory | Increase memory limits |
| Evicted | Node under pressure | Node resources, pod priority |
Debugging Commands
# Get pod status
kubectl get pod <pod-name> -o wide
# Describe pod (events, conditions)
kubectl describe pod <pod-name>
# Get logs
kubectl logs <pod-name>
kubectl logs <pod-name> -c <container> # specific container
kubectl logs <pod-name> --previous # previous crash
# Execute into pod
kubectl exec -it <pod-name> -- /bin/sh
# Get all events sorted by time
kubectl get events --sort-by='.lastTimestamp'
CrashLoopBackOff
Symptoms: Pod restarts repeatedly
Common Causes:
├─ Application error on startup
├─ Missing config/secrets
├─ Liveness probe failing too soon
├─ Resource limits too low
└─ Dependency not ready
Debug Steps:
1. kubectl logs <pod> --previous
2. kubectl describe pod <pod> # check events
3. Check liveness probe configuration
4. Check resource limits
5. Verify ConfigMaps/Secrets exist
ImagePullBackOff
Symptoms: Container image can't be pulled
Common Causes:
├─ Image doesn't exist
├─ Wrong image name/tag
├─ Private registry, missing credentials
├─ Registry rate limiting
└─ Network issues
Debug Steps:
1. Verify image name: kubectl describe pod <pod>
2. Try pulling manually: docker pull <image>
3. Check imagePullSecrets in pod spec
4. Verify secret exists: kubectl get secret <secret-name>
5. Check registry status
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 329 lines · 84 tokens per session scan A 560c4a12a28e
kubernetes-troubleshooting is a skill published in the GitHub repository latestaiagents/agent-skills (5 stars, last pushed 4mo ago), licensed MIT. It adds 84 tokens to every session and 1,804 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
pod-crashloop-triage
Use when pods are in CrashLoopBackOff, ImagePullBackOff, ErrImagePull, or OOMKilled — collects describe/logs/events and identifies the failure class before recommending a fix.
platform-sre-triage
Use when triaging platform reliability issues — orchestrates service health reporting, then Docker disk diagnostics, then the smallest safe next action.
ai-critique
A general diagnosis assistant for product, operations, technical, and software work. It analyzes supplied material and produces a summary, conclusions, action suggestions, and reusable deliverables.
ai-equipment-failure-rca-draft
A root-cause analysis draft assistant for investigating equipment failures. Root-cause analysis means looking for the underlying reason a failure happened, not only its visible symptom.
ai-performance
A performance diagnosis assistant for finding what may be slowing a service or product down.
ai-quality-complaint-8d-report
A business-diagnosis assistant for creating or reviewing an 8D report. An 8D report is a structured method for investigating a quality problem and documenting corrective action.