SKILLEMALL.ai

CC kubernetes-specialist

Use when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.

Jeffallan/claude-skills Agent Skills author: Jeffallan MIT 12 files body ≈ 1 812 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze…

As a process C 50/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureKubernetesInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
84
Quality 40%
92
Run on models
none yet
Process rating
C
50/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

    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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Dangerous commands cmd-pipe-to-shell references/multi-cluster.md:151
      Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation of a security skill)
      curl -Ls https://get.submariner.io | bash
      security skill
    • medium Dangerous commands cmd-pipe-to-shell references/service-mesh.md:9
      Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation of a security skill)
      curl -L https://istio.io/downloadIstio | sh -
      security skill
    • medium Dangerous commands cmd-pipe-to-shell references/service-mesh.md:322
      Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation of a security skill)
      curl --proto '=https' --tlsv1.2 -sSfL https://run.linkerd.io/install | sh
      security skill
    • low Dangerous commands cmd-privilege references/multi-cluster.md:12
      Privilege escalation / world-writable permissions (documentation of a security skill)
      chmod +x clusterctl && sudo mv clusterctl /usr/local/bin/
      security skill

    Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 50/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 7 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 33 steps, 2 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1812 tokens

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +3Description length 424: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 33 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (11 of 11)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.