SKILLEMALL.ai

BD device-control

Expose safe device actions (volume, brightness, open/close apps) for personal automation.

ClawHub Agent Skills author: iyeque v1.1.1 3 files body ≈ 532 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
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 · 0

✓ No critical or high findings

Files scanned: 3. 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 49/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (device-control) differs from the folder (iyeque-device-control)
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 10 steps
  • 100Execution cost. Instruction body is 532 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 89: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -220 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 10 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill is mostly transparent, but it lets an agent open programs and force-close matching processes on the user's computer, which needs review before installation.
LLM: suspicious (high) · VirusTotal: benign · 28 May 2026