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AC wireframe-mobile-flow

A lo-fi multi-screen MOBILE flow wireframe — three or four phone frames laid out in a row on a board, showing a connected user flow (Onboarding → Home feed → Item detail → Confirm). Grey-box content inside each device, dashed connector arrows + numbered step labels between screens, and a couple of annotation callouts. Reads like an app flow pinned to a whiteboard before any pixels are committed. Use when the brief asks for "mobile wireframe", "app flow", "user flow wireframe", "lo-fi mobile", "low fidelity", "线框图", "移动端线框", or "App 流程".

nexu-io/open-design Agent Skills author: nexu-io Apache-2.0 2 files body ≈ 751 tokens Open the sourcegithub.com↗ analyzed 6 d ago

A lo-fi multi-screen MOBILE flow wireframe — three or four phone frames laid out in a row on a board, showing a connected user flow (Onboarding → Home feed →…

As a process C 59/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureDesigntype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
59/100
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
This is a copy of a skill from another catalog; the rating counts the canonical one: wireframe-mobile-flow (nexu-io/open-design)

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

    • note frontmatter-key unknown frontmatter key "triggers"
    • note frontmatter-key unknown frontmatter key "od"

    Process rating: all ten parameters 59/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 751 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 542: enough signal without eating the budget
    • +4Structure: 3 headings
    • +3Step-by-step instructions: 16 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.