SKILLEMALL.ai

BD security-dashboard

Real-time security monitoring dashboard for OpenClaw and Linux server infrastructure. Monitors gateway status, network security, public exposure, system updates, SSH access, TLS certificates, and resource usage.

ClawHub Agent Skills author: vegasbrianc v1.2.1 9 files · 3 scripts body ≈ 1 991 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
98
Quality 40%
65
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 Dangerous commands cmd-background-process scripts/install.sh:88
    Starts a background / autostarted process
    systemctl enable $SERVICE_NAME
  • low Dangerous commands cmd-privilege SKILL.md:314
    Privilege escalation / world-writable permissions (documentation of a security skill)
    sudo rm /etc/systemd/system/security-dashboard.service
    security skill

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 8 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 85Steps. 91 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1991 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill

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
  • -2localhost URLs: will not work for another user
  • -215 emoji in the instructions: noise for the model
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 211: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 91 items
  • +4Has examples (22 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
The dashboard appears purpose-built for local security monitoring, but it needs Review because it installs a persistent service with broad passwordless sudo inspection rights and exposes detailed host-security data through an unauthenticated local API.
LLM: suspicious (high) · VirusTotal: benign · 28 May 2026