k8s-autoscaling

k8s-autoscaling is a skill for Claude Code, Codex from kudig-io/kudig-database. It costs 21 tokens per session (4,335 once invoked), scanned A, original, no licence file.

A diagnostic and repair guide for Kubernetes autoscaling. Autoscaling adjusts application or cluster capacity based on workload; HPA, VPA, and Cluster Autoscaler are Kubernetes autoscaling components.

In plain words
What is it for?
Use it to diagnose, repair, and verify HPA, VPA, or Cluster Autoscaler problems.
Why use it?
It helps investigate why autoscaling is not working and provides a process for fixing and verifying the result. The description does not specify particular failure causes.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to diagnose, repair, and verify HPA, VPA, or Cluster Autoscaler problems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kudig-io/kudig-database/k8s-autoscaling
Install

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.

Any agent
npx skills add kudig-io/kudig-database --skill k8s-autoscaling
Clone the repo
git clone --depth 1 https://github.com/kudig-io/kudig-database

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for k8s-autoscaling

README.md
[![agentmods](https://agentmods.dev/badge/skills/kudig-io/kudig-database/k8s-autoscaling/github.svg)](https://agentmods.dev/skills/kudig-io/kudig-database/k8s-autoscaling)
Your own site
<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.

agentmods 80×15 button for k8s-autoscaling

Your own site · 80×15
<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>
Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,335 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00021 $0.04335
Opus 5 $0.00010 $0.02167
Sonnet 5 $0.00004 $0.00867
Haiku 4.5 $0.00002 $0.00434

Measured today against content hash bc6cda2cd2af, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 today.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/diagnose-quick.sh, scripts/verify-autoscaling.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

19-故障诊断/08-技能体系/skill-set/k8s-autoscaling/SKILL.md · 342 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

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.

Changes

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.

  1. today Changed · +19 lines bc6cda2cd2af
  2. 12d ago First seen · 323 lines · 21 tokens per session scan A 7afa2a7549c4

Subscribe to this mod's changes

k8s-autoscaling is a skill published in the GitHub repository kudig-io/kudig-database (5 stars, last pushed yesterday), with no licence file. It adds 21 tokens to every session and 4,335 once invoked, about $0.0001 per session on Opus 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.

Related

Other skills, from other repositories

gke-ai-troubleshooting-jobset-interruption

Diagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or…

google/skills · 83 tokens

gke-workload-troubleshooting

Diagnoses GKE workload failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending, etc.) via logs and events. Use when pods fail to start or crash repeatedly. Don't use for GKE cluster infrastructure provisioning, node pool creation, or non-Kubernetes Google Cloud services.

google/skills · 69 tokens

gke-node-notready

Diagnoses GKE nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health. Don't…

google/skills · 112 tokens

gke-ai-troubleshooting-handle-disruption-gpu-tpu

Diagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing…

google/skills · 117 tokens

k8s-service-path

Trace the Kubernetes service path — Service to selector to pods to EndpointSlices to readiness, plus Ingress routing. Use when a service is getting no traffic, an ingress is not routing, or someone asks why a workload is unreachable inside a cluster.

automateyournetwork/netclaw · 55 tokens

incident-triage

Use when asked to triage, investigate, or diagnose a Kubernetes incident, outage, or unhealthy workload. Gives the step-by-step order of investigation and the format for the findings.

mezmo/aura · 41 tokens