SKILLEMALL.ai

BB k8s-manifest-generator

Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 7 files body ≈ 366 tokens Open the sourcegithub.com analyzed 2 d ago

Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims.

As a process B 68/100 · Nearly there — weak spots: result and completion, failures and branches, running it twice

ProcedureKubernetesInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
73
Run on models
none yet
Process rating
B
68/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: k8s-manifest-generator (sickn33/agentic-awesome-skills)

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Risky intent intent-offensive-security references/deployment-spec.md:484
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (test fixture / example file)
      - Disable privilege escalation
      fixture
    • low Risky intent intent-offensive-security resources/implementation-playbook.md:294
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - [ ] Disable privilege escalation

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "date_added"

    Process rating: all ten parameters 68/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 17 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 366 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)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 154: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 17 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.