SKILLEMALL.ai

AC mobizen-gui

Helps users set up and run MobiZen-GUI to perform mobile-use tasks — automating Android phone operations via natural language. Use when the user wants to control a phone, execute mobile-use tasks, install/configure MobiZen-GUI, deploy MobiZen-GUI-4B model, or customize the agent's input/output. Triggers on keywords like phone task, mobile-use, mobile automation, Android control, MobiZen, ADB, deploy model, run agent, configure model.

ClawHub Agent Skills author: xjx0524 v1.0.0 MIT-0 2 files body ≈ 1 776 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 56/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedureInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
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: 2. 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 56/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 8 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1776 tokens

    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)
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 437: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 8 items
    • +3Output format is stated explicitly
    • +4Has examples (16 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill matches its Android automation purpose, but it enables real phone control and model/API data flows without enough privacy and safety guardrails.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026