Capacitor Apple Review Preflight logo

Capacitor Apple Review Preflight

Organization
Cap-go
capacitor-apple-review-preflight

Guides the agent through an Apple App Store preflight review for Capacitor apps before submission or after rejection. Covers guideline checklist selection, App Store metadata review, Capacitor and iOS project inspection, privacy manifests, Sign in with Apple, entitlements, and common rejection patterns. Do not use for Google Play review, generic store publishing only, or non-Apple mobile runtimes.

Overview

PublisherCap-go
Repositorycapgo-skills
Skill namecapacitor-apple-review-preflight
Stars
71
Forks
4
Bundled files
23
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 23 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Cap-go on GitHub. Read the source before you install it.

Installation

Install the Capacitor Apple Review Preflight AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Cap-go/capgo-skills.git /tmp/capgo-skills
mkdir -p .claude/skills
cp -r /tmp/capgo-skills/plugins/capacitor-deployment/skills/capacitor-apple-review-preflight .claude/skills/capacitor-apple-review-preflight
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Capacitor Apple Review Preflight in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Capacitor Apple Review Preflight on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Capacitor Apple Review Preflight is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Capacitor Apple Review Preflight

Run a pre-submission or post-rejection Apple review audit for a Capacitor app.

This skill adapts the Apple guideline and rejection-rule corpus from truongduy2611/app-store-preflight-skills and narrows the workflow to Capacitor-specific project inspection.

When to Use This Skill

  • User wants an Apple App Store review preflight for a Capacitor app
  • User received an Apple rejection and wants the project audited against likely guideline failures
  • User wants to check metadata, entitlements, privacy manifests, Sign in with Apple, subscriptions, or minimum functionality before submission
  • User wants reviewer-notes guidance for a Capacitor iOS submission

Live Project Snapshot

Detected Capacitor, auth, subscription, analytics, and privacy-related packages: !node -e "const fs=require('fs');if(!fs.existsSync('package.json'))process.exit(0);const pkg=JSON.parse(fs.readFileSync('package.json','utf8'));const sections=['dependencies','devDependencies'];const out=[];for(const section of sections){for(const [name,version] of Object.entries(pkg[section]||{})){if(name.startsWith('@capacitor/')||name.startsWith('@capgo/')||name.includes('firebase')||name.includes('sentry')||name.includes('revenuecat')||name.includes('purchase')||name.includes('subscription')||name.includes('auth')||name.includes('analytics')||name.includes('segment')||name.includes('amplitude')||name.includes('mixpanel'))out.push(section+'.'+name+'='+version)}}console.log(out.sort().join('\n'))"

Relevant Apple review file paths: !find . -maxdepth 6 \( -name 'package.json' -o -name 'capacitor.config.json' -o -name 'capacitor.config.ts' -o -name 'capacitor.config.js' -o -name 'Info.plist' -o -name '*.entitlements' -o -name 'PrivacyInfo.xcprivacy' -o -name 'project.pbxproj' -o -path './ios' -o -path './fastlane/metadata' -o -path './metadata' \)

Procedure

Step 1: Confirm This Is the Right Review Scope

Use this skill for Apple-facing review work, not for generic publishing.

If the task is mostly about screenshots, release setup, or store upload mechanics, combine this skill with capacitor-app-store.

Step 2: Identify App Type and Load the Right Checklist

Always read:

  • references/guidelines/by-app-type/all_apps.md

Then add the checklist that matches the app:

  • subscription_iap.md for subscriptions or IAP
  • social_ugc.md for UGC or moderation-heavy apps
  • kids.md for Kids Category
  • health_fitness.md for health, fitness, or medical claims
  • games.md for games
  • ai_apps.md for AI or LLM features
  • crypto_finance.md for crypto, trading, or financial workflows
  • vpn.md for VPN and networking apps
  • macos.md only when the submission also targets macOS

Use references/guidelines/README.md for the full guideline index when a rejection cites a specific section.

Step 3: Inspect Capacitor and iOS Project State

Start from the injected snapshot above, then inspect:

  • package.json for Capacitor, auth, analytics, subscription, and SDK dependencies
  • capacitor.config.* for app identifiers, app name, web asset config, and live update settings
  • ios/App/App/Info.plist or the project-specific Info.plist
  • any *.entitlements files
  • PrivacyInfo.xcprivacy if present
  • fastlane/metadata or other local metadata directories if they exist

Pay special attention to Capacitor-specific Apple review risks:

  • social login providers without a Sign in with Apple path when required
  • heavy WebView-only apps that may trigger 4.2 minimum functionality concerns
  • third-party SDKs that imply Required Reason API declarations or privacy disclosures
  • native capabilities enabled in Xcode but not justified by shipped functionality
  • Capgo, Appflow, or other live-update flows that need clear reviewer notes and compliance boundaries
  • missing or vague usage strings for camera, photo library, microphone, location, notifications, Face ID, tracking, or local network access

Step 4: Run Rule-Based Review Passes

Use the upstream rule files as the source of truth:

  • metadata: references/rules/metadata/*.md
  • subscription: references/rules/subscription/*.md
  • privacy: references/rules/privacy/*.md
  • design: references/rules/design/*.md
  • entitlements: references/rules/entitlements/*.md

Map them onto the Capacitor app:

  • metadata rules against App Store text, screenshots, preview videos, and review notes
  • privacy rules against Info.plist, privacy manifests, SDK usage, and data collection flows
  • design rules against app navigation, native value, login flows, and reviewer accessibility
  • entitlements rules against enabled capabilities in the iOS project

If App Store metadata is not stored locally and asc is available, pull it with asc metadata pull --output-dir ./metadata. If not, audit local metadata sources and state what remains unverified.

Step 5: Produce a Capacitor-Focused Preflight Report

Use this format:

markdown
## Apple Review Preflight

### Rejections Found
- [GUIDELINE X.X.X] Issue summary
  - Evidence: file or metadata location
  - Why it matters for this Capacitor app
  - Fix: exact remediation

### Warnings
- [GUIDELINE X.X.X] Potential issue

### Passed
- [Category] Checks that looked clean

### Missing Inputs
- Metadata or review assets that were not available locally

Order findings by severity and make each fix concrete.

Step 6: Suggest Reviewer Notes and Submission Follow-Ups

When relevant, draft reviewer notes for:

  • demo accounts or test credentials
  • hidden or non-obvious features
  • hardware dependencies
  • subscription test flows
  • AI moderation or content controls
  • live-update behavior and what code can change post-review
  • reasons for special entitlements or network behavior

Error Handling

  • If app metadata is unavailable locally and asc is not configured, continue with the code and project audit and clearly mark metadata checks as partial.
  • If the app is mostly a thin web wrapper, call out guideline 4.2 risk directly rather than burying it in warnings.
  • If social login is present, verify whether guideline 4.8 requires Sign in with Apple before concluding the auth flow is review-safe.
  • If third-party SDKs suggest Required Reason API usage, inspect PrivacyInfo.xcprivacy before assuming privacy compliance.
  • If the user is asking how to fix a specific rejection, prioritize the cited guideline and only then expand to adjacent risks.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Capacitor Apple Review Preflight AI skill do?

Guides the agent through an Apple App Store preflight review for Capacitor apps before submission or after rejection. Covers guideline checklist selection, App Store metadata review, Capacitor and iOS project inspection, privacy manifests, Sign in with Apple, entitlements, and common rejection patterns. Do not use for Google Play review, generic store publishing only, or non-Apple mobile runtimes.

Why use Capacitor Apple Review Preflight on TypingMind?

Because you install it once and use it with any model. Capacitor Apple Review Preflight is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Capacitor Apple Review Preflight in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Cap-go/capgo-skills/tree/main/plugins/capacitor-deployment/skills/capacitor-apple-review-preflight. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Capacitor Apple Review Preflight?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Capacitor Apple Review Preflight?

As many as you like. As long as a model supports skills, you can use Capacitor Apple Review Preflight with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Capacitor Apple Review Preflight AI skill free?

It is published on GitHub by Cap-go. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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