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AB capacitor-deep-linking

Implements and debugs deep links in Capacitor apps - custom URL schemes, iOS Universal Links (apple-app-site-association, Associated Domains entitlement), Android App Links (assetlinks.json, autoVerify), and routing via @capacitor/app `appUrlOpen` + `App.getLaunchUrl()`. Covers the Capacitor 8.5+ UIScene change where AppDelegate `application(_:open:options:)` and `continue userActivity` stop being called and custom handling must move to SceneDelegate, plus cold vs warm launch testing. Use when links open Safari/Chrome instead of the app, `appUrlOpen` never fires, the launch URL is lost on cold start, or OAuth redirects do not return to the app. Do not use for the full UIScene migration (capacitor-uiscene-migration), push notification taps (capacitor-push-notifications), or social login plugin setup (capacitor-plugins).

Cap-go/capgo-skills Agent Skills author: Cap-go 6 files body ≈ 2 217 tokens Open the sourcegithub.com↗ analyzed 9 h ago

Implements and debugs deep links in Capacitor apps - custom URL schemes, iOS Universal Links (apple-app-site-association, Associated Domains entitlement)…

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

IntegrationSoftware developmenttype 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
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-deep-linking (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: 6. 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 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. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web, node) 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 2217 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 830: 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: 31 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)

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