SKILLEMALL.ai

BF vmware-aria

Use this skill whenever the user needs VMware Aria Operations (rebranded VMware VCF Operations in VCF 9 and later) data — performance metrics, alerts, capacity planning, anomaly detection, and automated reports. Directly handles: query resource metrics, list/acknowledge/cancel alerts, manage alert definitions, check capacity and time-remaining forecasts, detect anomalies, generate and manage reports. 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", or any Aria Operations / VCF Operations / vRealize Operations task. Combined with LLM, Aria data powers natural language reports: "give me a capacity report" → Aria collects data → LLM formats the report. 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 v1.11.0 MIT-0 8 files body ≈ 5 335 tokens Open the sourceclawhub.ai analyzed 9 h ago

Use this skill whenever the user needs VMware Aria Operations (rebranded VMware VCF Operations in VCF 9 and later) data — performance metrics, alerts…

As a process F 47/100 · Will not run — References files that are not bundled: ../vmware-pilot/SKILL.md, ../vmware-policy/SKILL.md

IntegrationGitHubData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
74
Run on models
none yet
Process rating
F
47/100
Will not run
References files that are not bundled: ../vmware-pilot/SKILL.md, ../vmware-policy/SKILL.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.

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.
  2. The text references files that are not there: add them or drop the references.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5335 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: ../vmware-pilot/SKILL.md
  • warning missing-ref reference to a missing file: ../vmware-policy/SKILL.md
  • note frontmatter-key unknown frontmatter key "installer"
  • note edit-residue the text marks something as outdated (lines 47): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: ../vmware-pilot/SKILL.md, ../vmware-policy/SKILL.md
  • 0Tools and files. 2 referenced file(s) missing: ../vmware-pilot/SKILL.md, ../vmware-policy/SKILL.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 19 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5335 tokens
  • 100Steps. 68 steps
  • 100When it triggers. States when to use and when not to
  • 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
  • low 14 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (14 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 992: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +4Description says when NOT to use the skill
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 68 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (4 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This is a coherent VMware Aria monitoring and management skill, but it installs an external Python package that uses Aria credentials and can perform audited alert/report writes.
LLM: benign (medium) · VirusTotal: · 12 Sept 2026