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 rohitg00/kubectl-mcp-server --skill k8s-autoscalinggit clone --depth 1 https://github.com/rohitg00/kubectl-mcp-serverWrote 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/rohitg00/kubectl-mcp-server/k8s-autoscaling)<a href="https://agentmods.dev/skills/rohitg00/kubectl-mcp-server/k8s-autoscaling"><img src="https://agentmods.dev/badge/skills/rohitg00/kubectl-mcp-server/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/rohitg00/kubectl-mcp-server/k8s-autoscaling"><img src="https://agentmods.dev/badge/skills/rohitg00/kubectl-mcp-server/k8s-autoscaling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00039 | $0.01404 |
| Opus 5 | $0.00019 | $0.00702 |
| Sonnet 5 | $0.00008 | $0.00281 |
| Haiku 4.5 | $0.00004 | $0.00140 |
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 11d 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 — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kubernetes Autoscaling
Comprehensive autoscaling using HPA, VPA, and KEDA with kubectl-mcp-server tools.
When to Apply
Use this skill when:
- User mentions: "HPA", "VPA", "KEDA", "autoscale", "scale to zero"
- Operations: configuring autoscaling, checking scaling status
- Keywords: "scale automatically", "event-driven", "right-size"
Priority Rules
| Priority | Rule | Impact | Tools |
|---|---|---|---|
| 1 | Verify metrics-server for HPA | CRITICAL | get_resource_metrics |
| 2 | Set resource requests before HPA | CRITICAL | describe_pod |
| 3 | Use KEDA for scale-to-zero | HIGH | keda_scaledobjects_list_tool |
| 4 | Check VPA recommendations | MEDIUM | get_resource_recommendations |
Quick Reference
| Task | Tool | Example |
|---|---|---|
| List KEDA ScaledObjects | keda_scaledobjects_list_tool |
keda_scaledobjects_list_tool(namespace) |
| Get ScaledObject | keda_scaledobject_get_tool |
keda_scaledobject_get_tool(name, namespace) |
| List ScaledJobs | keda_scaledjobs_list_tool |
keda_scaledjobs_list_tool(namespace) |
| Check KEDA | keda_detect_tool |
keda_detect_tool() |
HPA (Horizontal Pod Autoscaler)
Basic CPU-based scaling:
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: my-app-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
Apply and verify:
kubectl_apply(hpa_yaml, namespace)
get_hpa(namespace)
VPA (Vertical Pod Autoscaler)
Right-size resource requests:
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: my-app-vpa
spec:
targetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
updatePolicy:
updateMode: "Auto"
KEDA (Event-Driven Autoscaling)
Detect KEDA Installation
What ships with it
3 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.
- 11d ago First seen · 237 lines · 39 tokens per session scan A 1aa9a3995f43
k8s-autoscaling is a skill published in the GitHub repository rohitg00/kubectl-mcp-server (956 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 1,404 once invoked, about $0.0002 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 2026-08-30.
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