SKILLEMALL.ai

AC design-md-ui-designer

Use when designing or improving web, app, extension, community, course, video-ideation, marketing landing, SEO content hub, or public policy-page UI with a DESIGN.md-backed design system, high-end media assets, responsive screenshots, accessibility checks, trust-building conversion copy, and high-quality AI-generated raster imagery when useful. Trigger when the user mentions DESIGN.md, design.md, designdotmd.directory, UI design skill, landing page, conversion page, Pages UI polish, community media, video ideation assets, design tokens, visual redesign, or gpt-image-2-2026-04-21 as designer.

ClawHub Agent Skills author: Zakhar Pashkin v1.0.1 MIT-0 5 files body ≈ 3 840 tokens Open the sourceclawhub.ai analyzed 31 h ago

md-backed design system, high-end media assets, responsive screenshots, accessibility checks, trust-building conversion copy, and high-quality AI-generated…

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureCloudflareDesignMedia and videoMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 11 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 91 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3840 tokens
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 598: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 91 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    The skill appears to be a broad design-workflow helper, and the available evidence does not show hidden, destructive, or data-stealing behavior.
    LLM: benign (medium) · VirusTotal: · 10 Jun 2026