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AC capgo-native-builds

Use for Capgo Cloud Build (Capgo Build) native iOS and Android workflows, including CLI login and API-key precedence, `build init` onboarding, signing credential save/update/export, `build request` with TestFlight, App Store, or Play upload, temporary IPA/APK/AAB download links (`--output-upload`), prescan failures, `build needed` OTA-vs-native gating, and CI secrets. Use when errors mention "No credentials found for this app and platform", "Legacy provisioning profile format detected", "Missing required argument: --platform", or prescan check ids. Do not use for OTA bundle uploads (capgo-release-management), updater plugin setup (capgo-live-updates), or local Xcode/Gradle builds and generic CI runners (capacitor-ci-cd).

Cap-go/capgo-skills Agent Skills author: Cap-go 4 files body ≈ 2 742 tokens Open the sourcegithub.com↗ analyzed 8 h ago

Use for Capgo Cloud Build (Capgo Build) native iOS and Android workflows, including CLI login and API-key precedence, build init onboarding, signing…

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorSoftware 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
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
97
Run on models
none yet
Process rating
C
60/100
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

The same skill appears in 1 more place: 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    • note edit-residue the text marks something as outdated (lines 143): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 60/100

    • 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. 11 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. 45 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 2742 tokens
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (4 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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 730: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 45 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: 97.