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AC tailwind-capacitor

Sets up and uses Tailwind CSS v4 in Capacitor apps - CSS-first config (`@import "tailwindcss"`, `@theme`, `@utility`, `@custom-variant`, `@source`, `@plugin`), `@tailwindcss/vite` / `@tailwindcss/postcss`, upgrading from v3 `tailwind.config.js` with `npx @tailwindcss/upgrade`, WebView browser floor (Safari 16.4+ / Chrome 111+ vs Capacitor iOS 15/16 targets), safe-area utilities built on `env(safe-area-inset-*)`, platform variants (`ios:`/`android:` via a root class), class-based dark mode, `pointer-coarse:` touch targets, and hover-on-touch behavior. Use when installing Tailwind in a Capacitor project, styles do not apply after upgrading to v4, colors look wrong on older iPhones, or building mobile layouts with Tailwind. Do not use for Konsta UI components (konsta-ui), Ionic theming (ionic-design), native system bar / edge-to-edge config (safe-area-handling), or keyboard overlap (capacitor-keyboard).

Cap-go/capgo-skills Agent Skills author: Cap-go 4 files body ≈ 1 681 tokens Open the sourcegithub.com↗ analyzed 9 h ago

Sets up and uses Tailwind CSS v4 in Capacitor apps - CSS-first config (@import "tailwindcss", @theme, @utility, @custom-variant, @source, @plugin)…

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

ProcedureInfrastructureData and analyticsMarketingtype 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%
89
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: tailwind-capacitor (Cap-go/capgo-skills)

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: 4. 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

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 85Steps. 34 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1681 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
    • +3Description length 913: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 34 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

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