SKILLEMALL.ai

DC nas-dashboard

(no description)

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: wudi488 v3.0.1 MIT-0 5 files · 2 scripts body ≈ 3 765 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ReferenceDockerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
D
49/100
safety, quality, tests
Safety 60%
81
Quality 40%
0
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
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

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Add a description to the frontmatter: without it the skill never triggers.
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

  • high Dangerous commands cmd-persistence scripts/collect.sh:368
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    if [ -f /etc/cron.d/timeshift-hourly ] || systemctl is-active timeshift.timer &>/dev/null || [ "$TS_COUNT" -gt 0 ] 2>/dev/null; then
Medium and low: 1
  • low Dangerous commands cmd-background-process scripts/format.py:161
    Starts a background / autostarted process (string literal in code, not executed)
    '','如需NFS: sudo systemctl enable --now nfs-server',''))
    code literal

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 61/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 30Running it twice. 11 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 102 steps
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3765 tokens
  • 100Progress reporting. Reports progress

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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2112 emoji in the instructions: noise for the model
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 102 items
  • +4Has examples (21 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: clean
This NAS monitoring skill is broad and privacy-sensitive, but its collection, sudo reads, formatting, and optional Telegram delivery fit the stated dashboard purpose and are mostly disclosed.
LLM: benign (high) · VirusTotal: · 31 May 2026