SKILLEMALL.ai

AB vmware-aria

Use this skill whenever the user needs VMware Aria Operations (VMware VCF Operations in VCF 9+) data — metrics, alerts, capacity, anomalies, reports. Directly handles: resource metrics plus metric key/property/relationship lookup, list/acknowledge/cancel alerts with notes and recommendations, alert definitions, capacity forecasts, anomalies, reports, resource maintenance mode, Aria's own node health and adapter collection state. Always use this skill for "check vSphere capacity", "what Aria Operations alerts are active", "show VMware anomalies", "generate an Aria report", "rightsizing recommendations", "VCF Operations alerts", "put this host in Aria maintenance mode", "is Aria Operations still collecting from vCenter", "what does Aria recommend for this alert", or any Aria Operations / VCF Operations / vRealize Operations task. Do NOT use for real-time vCenter alarms/events (use vmware-monitor), VM operations (use vmware-aiops), or NSX networking (use vmware-nsx). For load balancing/AVI/AKO use vmware-avi.

ClawHub Agent Skills author: wei zhou v1.13.0 MIT-0 9 files body ≈ 5 437 tokens Open the sourceclawhub.ai analyzed 8 h ago

Directly handles: resource metrics plus metric key/property/relationship lookup, list/acknowledge/cancel alerts with notes and recommendations, alert…

As a process B 73/100 · Nearly there — weak spots: result and completion, inputs and preconditions

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
83
Run on models
none yet
Process rating
B
73/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Execution cost w 6
70
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.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5437 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "installer"

Process rating: all ten parameters 73/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 70Execution cost. Instruction body is 5437 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 40 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (13 tags): a typed call is more reliable
  • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

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

  • +3Description length 1021: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 9 example trigger phrases
  • +4Description says when NOT to use the skill
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

External checks

ClawHub: clean
This skill is a disclosed VMware Aria Operations integration, but it should be installed with least-privilege credentials because it can make some monitoring changes.
LLM: benign (medium) · VirusTotal: · 13 Sept 2026