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AC safe-area-handling

Fixes notch, Dynamic Island, home indicator, display cutout, and system bar overlap in Capacitor apps. Covers `viewport-fit=cover` + `env(safe-area-inset-*)`, the Capacitor 8 SystemBars core plugin (`insetsHandling`, injected `--safe-area-inset-*` CSS variables for Android WebView < 140, removal of `android.adjustMarginsForEdgeToEdge`), Android 15/16 enforced edge-to-edge (`overlaysWebView` and `backgroundColor` of @capacitor/status-bar no longer work at targetSdk 36), iOS `contentInset`, and insets that change at runtime on rotation, iPad/foldable resizable windows. Use when headers sit under the status bar, tab bars hide behind the gesture bar, `env()` returns 0 on Android, or layout broke after upgrading to Capacitor 8 / targetSdk 35+. Do not use for keyboard overlap (capacitor-keyboard), Ionic/Konsta component theming (ionic-design, konsta-ui), Tailwind utility setup (tailwind-capacitor), or iOS multi-window/resizability adoption (capacitor-ios-resizability).

Cap-go/capgo-skills Agent Skills author: Cap-go 4 files body ≈ 2 063 tokens Open the sourcegithub.com↗ analyzed 9 h ago

Fixes notch, Dynamic Island, home indicator, display cutout, and system bar overlap in Capacitor apps.

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSoftware developmentData and analyticsDesigntype 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
58/100
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: safe-area-handling (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

    • note edit-residue the text marks something as outdated (lines 38): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 58/100

    • 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. 8 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 35 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 2063 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 977: 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: 35 items
    • +4Has examples (5 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.