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 kudig-io/kudig-database --skill openclaw-workspacegit clone --depth 1 https://github.com/kudig-io/kudig-databaseWrote 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/kudig-io/kudig-database/openclaw-workspace)<a href="https://agentmods.dev/skills/kudig-io/kudig-database/openclaw-workspace"><img src="https://agentmods.dev/badge/skills/kudig-io/kudig-database/openclaw-workspace/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/kudig-io/kudig-database/openclaw-workspace"><img src="https://agentmods.dev/badge/skills/kudig-io/kudig-database/openclaw-workspace.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 | $0.00011 | $0.04667 |
| Opus 5.5 | $0.00004 | $0.01867 |
| Sonnet 5.5 | $0.00002 | $0.00933 |
| Haiku 4.5 | $0.00001 | $0.00467 |
Grade A, and why
openclaw-workspace 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 1mo 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 net-test --image=busybox:1.36 --rm -it --restart=Never -- wget -qO- --timeout=5 http://<svc>.<ns>:<port> Copies of this mod
1 near-identical copy found in the catalogue:
- k8s-pvc-storage — 98% identical, 19 lines differ
How it starts
The opening of the file, as written. The whole thing — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.
生产环境安全提示
本文档包含可直接执行的运维命令。执行前请确认:当前目标集群与 Namespace 是否正确;是否具备足够的 RBAC 权限;是否已在非生产环境验证。命令风险等级标注:🔴 高风险(可能造成数据丢失或服务中断)、🟡 中风险(会修改集群状态,但通常可回滚)、🟢 低风险/只读(信息收集,无副作用)。
title: K8S 运维诊断技能库 description: [[kubernetes|Kubernetes]] 运维诊断全栈技能库,涵盖 Pod/Node/Network/Storage/Performance 五大故障域的结构化 SOP category: ai-agent tags:
- ai
- agent
- llm
- rag
- multi-agent
- [[etcd|etcd]]
- apiserver
- [[kubelet|kubelet]]
- [[prometheus|prometheus]]
- coredns last_updated: 2026-04 difficulty: advanced reading_level: advanced audience:
- AI 工程师
- 架构师
- SRE estimated_read_time: 5min intent_queries:
- K8S 运维诊断技能库 是什么
- 如何 K8S 运维诊断技能库 trigger_keywords:
- K8S
- 运维诊断技能库
- ai
- agent authors:
- name: KUDIG Team role: contributor k8s_versions:
- '1.28'
- '1.29'
- '1.30'
- '1.31'
- '1.32'
K8S 运维诊断技能库
1. 技能覆盖范围
技能域全景:
├── Pod 故障域
│ ├── Pending(调度失败)
│ ├── CrashLoopBackOff(崩溃循环)
│ ├── OOMKilled(内存溢出)
│ ├── ImagePullBackOff(镜像拉取失败)
│ ├── Error / Unknown(其他异常)
│ └── Evicted(被驱逐)
│
├── Node 故障域
│ ├── NotReady(节点不就绪)
│ ├── MemoryPressure / DiskPressure / PIDPressure
│ ├── NetworkUnavailable
│ └── SchedulingDisabled
│
├── Network 故障域
│ ├── Service 不通
│ ├── DNS 解析失败
│ ├── Pod 间通信异常
│ ├── Ingress 不可达
│ └── NetworkPolicy 拦截
│
├── Storage 故障域
│ ├── PVC Pending
│ ├── 挂载失败
│ └── CSI 驱动异常
│
└── Performance 故障域
├── API Server 延迟高
├── etcd 延迟高
├── 调度延迟
└── 网络延迟
2. Pod 故障诊断 SOP
2.1 Pod Pending
触发条件: Pod 状态为 Pending 超过 30 秒
# 🟢 低风险:只读/信息收集,通常无副作用
# Step 1: 确认状态
kubectl get pod <pod> -n <ns> -o wide
# Step 2: 查看事件(关键!事件中有调度失败原因)
kubectl describe pod <pod> -n <ns> | tail -20
kubectl get events -n <ns> --field-selector involvedObject.name=<pod> --sort-by=.lastTimestamp
# Step 3: 根据事件分支诊断
| 事件关键词 | 根因 | 修复方向 |
|---|---|---|
Insufficient cpu/memory |
节点资源不足 | 扩容节点 / 调整 requests |
node(s) didn't match selector |
NodeSelector 不匹配 | 检查标签 / 修改选择器 |
node(s) had taint |
Taint/Toleration 不匹配 | 添加 Toleration / 移除 Taint |
persistentvolumeclaim not found |
PVC 未绑定 | 检查 PVC 状态和 StorageClass |
Unschedulable |
节点不可调度 | 检查节点 SchedulingDisabled |
pod has unbound immediate PVC |
PVC 立即绑定未就绪 | 等待 PVC Ready 或检查 PV |
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · +19 lines ad831aea2a6f
- 1mo ago First seen · 406 lines · 11 tokens per session scan A bc69fe7fdeca
openclaw-workspace is a skill published in the GitHub repository kudig-io/kudig-database (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 11 tokens to every session and 4,667 once invoked, about $0.0000 per session on Opus 5.5. 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
docker-debug
Debug Kurtosis running on local Docker. Inspect engine, API container, and service logs. Diagnose container crashes, port conflicts, and networking issues. Use when kurtosis commands fail or services aren't reachable on Docker.
k8s-debug-pods
Debug Kurtosis pods on Kubernetes. Diagnose why pods are Pending, CrashLoopBackOff, ImagePullBackOff, or Evicted. Check node taints, tolerations, resource pressure, and pod events. Use when kurtosis engine start fails or pods aren't coming online.
networkpolicy-debug
Diagnose NetworkPolicy-related connectivity issues (traffic unexpectedly blocked, default-deny effects, egress blocking DNS). Identifies which NetworkPolicies affect a pod, checks ingress/egress rules, and verifies CNI support.
statefulset-debug
Diagnose StatefulSet rollout and scaling failures (ordered update stuck, OnDelete not updating, partition misconfiguration, PVC binding deadlocks). Checks update strategy, pod ordinal progression, PVC bindings, and ordered startup to identify why a StatefulSet is not progressing.
image-pull-debug
Diagnose container image pull failures (ErrImagePull / ImagePullBackOff). Checks pod status, containerd logs, and events to identify root cause.
pod-pending-debug
Diagnose pod scheduling failures (Pending, Unschedulable). Checks events, node resources, taints, affinity, and PVC bindings to identify why a pod cannot be scheduled.