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 k8s-autoscalinggit 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/k8s-autoscaling)<a href="https://agentmods.dev/skills/kudig-io/kudig-database/k8s-autoscaling"><img src="https://agentmods.dev/badge/skills/kudig-io/kudig-database/k8s-autoscaling/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/k8s-autoscaling"><img src="https://agentmods.dev/badge/skills/kudig-io/kudig-database/k8s-autoscaling.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 | $0.00021 | $0.04335 |
| Opus 5.5 | $0.00008 | $0.01734 |
| Sonnet 5.5 | $0.00004 | $0.00867 |
| Haiku 4.5 | $0.00002 | $0.00434 |
Grade A, and why
k8s-autoscaling scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 342 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）。
K8s Autoscaling Failure 诊断与修复
HPA、VPA 和 Cluster Autoscaler 是 [[kubernetes|Kubernetes]] 弹性能力的核心组件。当自动扩缩容不工作时，应用可能因负载突增而响应缓慢，或因资源浪费而成本过高。
本 [[SKILL|Skill]] 覆盖 HPA 无法获取指标、VPA 推荐不生效、Cluster Autoscaler 无法扩展节点等全部常见根因的诊断和修复。
何时使用此 Skill
| 症状 | 检测方法 | 置信度 |
|---|---|---|
HPA TARGET 显示 <unknown> |
kubectl get hpa |
0.95 |
| HPA 不随负载变化扩缩容 | 压测时观察 kubectl get hpa |
0.90 |
| ClusterAutoscaler Pod 异常 | `kubectl get [[Pods | pods]] -n kube-system |
| VPA recommendation 为空 | kubectl get vpa |
0.85 |
unable to get metrics 事件 |
kubectl describe hpa |
0.95 |
排除条件: 节点 NotReady → SKILL-NODE-001; 资源配额 → SKILL-RBAC-001
快速分级（2 分钟内完成）
影响范围
├── 核心服务高负载无法扩容 ──────→ P0（15min 内修复）
├── 生产环境成本异常（无法缩容） ─→ P1（30min 内修复）
├── 新 HPA/VPA 规则不生效 ──────→ P2（2h 内修复）
└── 测试环境扩缩容问题 ──────────→ P3（4h 内处理）
立即升级条件:
- 核心服务因无法扩容导致大面积超时
- Cluster Autoscaler 导致节点异常增加/减少
- metrics-server 完全不可用
执行流程
# 🟢 低风险：只读/信息收集，通常无副作用
工单/告警触发
│
▼
┌──────────────┐ 脚本: scripts/diagnose-quick.sh
│ Phase 1 │ 内容: kubectl 快速检查（只读）
│ 快速检查 │ Step: D1.1-D1.5
└──────┬───────┘
│ 确认根因
▼
┌──────────────┐ 参考: reference/remediation-playbook.md
│ 修复操作 │ 风险: LOW → MEDIUM → HIGH
│ REM-001~005 │
└──────┬───────┘
│
▼
┌──────────────┐ 脚本: scripts/verify-autoscaling.sh
│ 验证确认 │ 检查: HPA/VPA/CA 状态
└──────────────┘
可用脚本
| 脚本 | 用途 | 参数 | 风险 |
|---|---|---|---|
scripts/diagnose-quick.sh |
自动扩缩容快速诊断 | NAMESPACE HPA_NAME (optional) |
只读 |
scripts/verify-autoscaling.sh |
修复后验证 | NAMESPACE HPA_NAME (optional) |
只读 |
根因概览 (5 种)
| RC ID | 根因 | 概率 | 首选修复 | 风险 |
|---|---|---|---|---|
| RC-001 | metrics-server 未安装或异常 | 高 | REM-001 修复 metrics-server | MEDIUM |
| RC-002 | HPA 指标配置错误 | 高 | REM-002 修正 HPA 配置 | LOW |
| RC-003 | VPA admission webhook 问题 | 中 | REM-003 重启 VPA | MEDIUM |
| RC-004 | Cluster Autoscaler 权限/配置错误 | 中 | REM-004 修复 CA | MEDIUM |
| RC-005 | 资源配额或节点池限制 | 中 | REM-005 调整限制 | LOW |
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 bc6cda2cd2af
- 1mo ago First seen · 323 lines · 21 tokens per session scan A 7afa2a7549c4
k8s-autoscaling is a skill published in the GitHub repository kudig-io/kudig-database (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 21 tokens to every session and 4,335 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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