SKILLEMALL.ai

AC capacitor-app-upgrade-v7-to-v8

Upgrades a Capacitor app from v7 to v8 using `npx cap migrate` from `@capacitor/cli@latest`, then the manual checklist - Node 22+, Xcode 26+, iOS deployment target 15.0, Android Studio Otter, AGP 8.13.0, Gradle 8.14.3, JDK 21, minSdk 24, compile/target SDK 36, Kotlin 2.2.20, Gradle `=` property assignment syntax, `density` in configChanges, removed `android.adjustMarginsForEdgeToEdge` (use the System Bars plugin and CSS env vars), `bridge_layout_main.xml` renamed, iOS `appendUserAgent` whitespace fix, and official plugin changes (Geolocation timeout, Screen Orientation/Barcode Scanner on Android 16 large screens). Use when `@capacitor/core` is 7.x and the target is 8.x. Points to the 8.5 UIScene adoption and v9 next steps. Do not use for other major versions, plugin library upgrades, or non-Capacitor apps.

Cap-go/capgo-skills Agent Skills author: Cap-go 4 files body ≈ 1 767 tokens Open the sourcegithub.com↗ analyzed 10 h ago

Upgrades a Capacitor app from v7 to v8 using npx cap migrate from @capacitor/cli@latest, then the manual checklist - Node 22+, Xcode 26+, iOS deployment…

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
99
Quality 40%
89
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: capacitor-app-upgrade-v7-to-v8 (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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Broad scope meta-dynamic-shell SKILL.md:28
      Shell command executed automatically when the skill loads (Claude Code !`cmd` preamble)
      !`node -e "const fs=require('fs');if(!fs.existsSync('package.json'))process.exit(0);const pkg=JSON.parse(fs.readFileSync('package.json','utf8'));const out=[];for(const section of ['dependencies','devD

    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 61/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 9 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 21 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1767 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    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 817: 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: 21 items
    • +4Has examples (3 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.