SKILLEMALL.ai
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AC screen-off

Toggle any macOS display on/off by ID, name, or index.

ClawHub Hermes author: Ming Fang v1.0.0 MIT-0 5 files body ≈ 268 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Toggle any macOS display on/off by ID, name, or index.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
51/100
Has gaps
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

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 51/100

    • 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
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Consistency. The Hermes dialect needs category and tags
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 5 steps
    • 100Execution cost. Instruction body is 268 tokens
    • 100Running it twice. No mutating operations

    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 54: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    This skill is a disclosed macOS display-control utility, but users should handle force and permanent modes carefully because they can leave a Mac without a visible display.
    LLM: benign (high) · VirusTotal: · 30 Aug 2026