SKILLEMALL.ai

AB k8s-cost-optimizer

Find and rank Kubernetes cost-saving opportunities from kubectl, metrics-server, kube-state-metrics, and cloud billing. Identifies overprovisioned CPU/memory requests and limits, idle namespaces and workloads, oversized PersistentVolumes, unused LoadBalancer services, expensive node types, missing HorizontalPodAutoscalers, and clusters that haven't adopted spot/preemptible/Graviton nodes. Outputs a ranked list of recommendations with $/month savings estimates and ready-to-apply YAML patches. Covers EKS, GKE, and AKS specifics including instance pricing, savings plans, committed-use discounts, and reservation strategies. Use when asked to cut a Kubernetes cloud bill, right-size workloads, plan a spot migration, build a FinOps report, or tune HPA settings. Triggers on "kubernetes cost", "k8s cost", "eks cost", "gke cost", "aks cost", "right-size", "rightsize", "kubecost", "opencost", "vpa", "hpa", "spot instances", "preemptible", "savings plan", "node pool", "pod requests", "finops".

ClawHub Agent Skills author: charlie-morrison v1.0.0 MIT-0 2 files body ≈ 5 443 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, running it twice

GeneratorKubernetesInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5443 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 68/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 21 mutating operations with no state check
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5443 tokens
  • 100Steps. 45 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 996: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 15 example trigger phrases
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 45 items
  • +3Output format is stated explicitly
  • +4Has examples (22 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This is a disclosed, instruction-only Kubernetes cost-audit skill, but its recommendations should be reviewed before applying to production clusters or cloud spend.
LLM: benign (high) · VirusTotal: · 29 May 2026