This project provides an AI agent skill designed to proactively scan iOS and macOS projects for common App Store rejection patterns. It targets developers aiming to reduce submission failures by identifying potential violations in source code, metadata, and configurations before the app reaches Apple's review process.

How It Works

The skill begins by identifying the app's type to load a relevant checklist from its extensive index of Apple's guidelines. It then leverages the asc CLI to pull necessary App Store metadata. Subsequently, it scans the project against a comprehensive set of rejection rules, meticulously organized by categories such as metadata, subscriptions, privacy, design, and entitlements. Each finding is reported with its severity, affected files, and suggested resolution steps, including an "Autofix + Validate" feature for automated corrections.

Quick Start & Requirements

• Install: npx skills add truongduy2611/app-store-preflight-skills
• Prerequisites: Requires the asc CLI, which can be installed via brew install asc. Metadata is typically pulled using asc metadata pull --app "<APP_ID>" --version "<VERSION>" --dir ./metadata.
• Documentation: Detailed guideline references are available within the references/guidelines/README.md path in the repository.

Highlighted Details

• Features a comprehensive index covering over 100 Apple Review Guidelines, supplemented by 10 app-type specific checklists (e.g., Kids, Games, AI Apps, VPN).
• Rejection rules are systematically organized into categories: Metadata, Subscriptions, Privacy, Design, and Entitlements, each linked to specific Apple guideline numbers.
• Offers an "Autofix + Validate" capability, allowing for automated application of fixes and subsequent re-running of checks.
• Integrates seamlessly with the asc CLI for efficient metadata management and pulling.

Maintenance & Community

The provided README does not contain specific information regarding notable contributors, sponsorships, or community channels such as Discord or Slack.

Licensing & Compatibility

• License: MIT License.
• Compatibility: The permissive MIT license generally supports commercial use and integration within closed-source projects without significant restrictions.

Limitations & Caveats

The tool's efficacy is contingent upon the accuracy of the asc CLI's metadata extraction and the completeness of the skill's internal rule set. Complex or nuanced rejection scenarios may still require manual developer intervention, as the autofix feature might not cover all edge cases. The knowledge base is strictly limited to the rules and guidelines explicitly defined within the repository.