SKILLEMALL.ai

AB capacitor-performance

Diagnoses and fixes performance problems specific to Capacitor apps - slow cold start or long splash, white screen after camera/backgrounding (WKWebView "WebView process terminated" reload, Android onRenderProcessGone), large base64 payloads over the native bridge (Camera, Filesystem.readFile, CapacitorHttp), jank in the WebView, memory growth from unremoved plugin listeners, oversized Preferences storage, slow Android WebView versions, and debug logging left on in release. Covers profiling with Safari Web Inspector, chrome://inspect, Xcode Instruments, Android Studio Profiler, and adb timing commands. Do not use for crash/stack-trace debugging (use debugging-capacitor or capacitor-native-observability), device log capture (use ios-android-logs), offline data architecture (use capacitor-offline-first / sqlite-to-fast-sql), splash configuration details (use capacitor-splash-screen), or generic web performance unrelated to Capacitor.

Cap-go/capgo-skills Agent Skills author: Cap-go 3 files body ≈ 1 851 tokens Open the sourcegithub.com↗ analyzed 8 h ago

Diagnoses and fixes performance problems specific to Capacitor apps - slow cold start or long splash, white screen after camera/backgrounding (WKWebView…

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
B
65/100
Nearly there
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-performance (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: 3. 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    • note edit-residue the text marks something as outdated (lines 46): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 65/100

    • 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. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 100Steps. 31 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1851 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
    • +3Description length 945: 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: 8 headings
    • +3Step-by-step instructions: 31 items
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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