SKILLEMALL.ai

AC mosocanvas

Evidence-based visual direction for zero-reference or reference-led campaign images, posters, social image series, and physical promotional collateral. Use when Codex must turn an intent into authored shots, composition boards, visual narrative, color/light scripts, trend-informed mechanisms, independent artifact reviews, controlled repairs, or blind quality benchmarking against leading image generators such as Midjourney. Do not use for mechanical conversion, UI/product-flow design, pure retouching without art-direction decisions, or visual claims about an artifact that cannot be inspected.

ClawHub Agent Skills author: Moso v0.1.0 MIT-0 59 files body ≈ 2 886 tokens Open the sourceclawhub.ai analyzed 2 d ago

Evidence-based visual direction for zero-reference or reference-led campaign images, posters, social image series, and physical promotional collateral.

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ReferenceSoftware developmentMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
60/100
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
    • 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: 57. 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 60/100

    • 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. 3 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 77 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2886 tokens
    • low No test case covers injection arriving through data

    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
    • +3Output format is not stated: the model decides each time
    • -33 of 18 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 598: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 77 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (15 of 15)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This skill is a coherent visual-direction workflow with local helper scripts and no evidence of hidden persistence, credential access, exfiltration, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 28 Jul 2026