AI wrapper scrutiny — AI-powered apps with minimal native value may face rejection

Apple issued explicit guidance in 2023–2024 that apps must provide lasting value beyond a thin AI API wrapper. An app consisting of a text input, an LLM API call, and a text output display — with no system prompt specialization, no caching, no offline capability, and no native device integration — is functionally equivalent to accessing the underlying model through a web browser. Both stores are actively scrutinizing AI apps under this lens. NIST AI RMF MAP-1.5 classifies thin-wrapper deployment as a governance gap because the developer has minimal insight into or control over the AI's behavior relative to the app's stated purpose.

Add at least one of the following to distinguish the app from a web-equivalent AI interface before submission:

• Offline response caching: Store recent AI responses in SQLite or AsyncStorage so the app is useful without a network connection
• Native device integration: Feed camera input, voice, calendar events, or HealthKit data into the AI prompt to provide context a web interface cannot
• Personalized memory: Persist user preferences, prior session context, or domain-specific settings that shape AI behavior over time
• Structured multi-step workflow: Replace the open-ended chat interface with a guided flow that breaks a complex task into discrete native steps

// src/config/ai.ts — minimal domain specialization
const SYSTEM_PROMPT = `You are a [specific domain] expert assistant.
Context: The user is [specific persona/use case].
Scope: Answer only questions about [narrow domain]. Decline off-topic requests.`;

Domain-specific system prompts are table stakes — a generic GPT wrapper with no prompt engineering provides no value a user cannot get from ChatGPT.com directly.

• ID: ai-wrapper-scrutiny

• Severity: info

• What to look for: Count all relevant instances and enumerate each. If AI integration is detected, assess whether the app's primary value is thin API wrapping around a foundation model with no significant native functionality added: (1) Does the app consist primarily of a text input, an AI API call, and a text output display? (2) Is there any caching, offline capability, personalization, structured workflow, or domain-specific prompting that adds value beyond the raw API? (3) Does the app use a generic GPT/Claude/Gemini API call with no system prompt specialization, or does it have a thoughtfully crafted domain-specific prompt? (4) Are there any native device integrations (camera, voice, health, calendar) that justify the app being native rather than a website? Apple has issued guidance (2023-2024) that apps must provide lasting value beyond a thin AI API wrapper. Both stores scrutinize AI-powered apps more heavily. This is informational — a thin wrapper is not an automatic rejection but significantly increases review scrutiny. Skip this check if the app has substantial native functionality beyond the AI integration.

• Pass criteria: App has substantial native functionality beyond the AI integration (native device integrations, significant offline capability, complex structured workflow, meaningful personalization). At least 1 implementation must be verified. Or the AI integration is a secondary feature, not the entire app. Result is pass or skip only — never fail.

• Fail criteria: Not applicable — this is an informational check. Result is pass or skip only.

• Skip (N/A) when: No AI or LLM integration detected. Or the app clearly has substantial native value that is not dependent on AI (AI is a secondary feature).

• Detail on fail: Not applicable — result is pass or skip only.

• Remediation: If the app's primary value is AI-powered, add at least one of: offline caching of responses, personalized memory of user preferences, native device integration (camera input, voice, calendar access), a structured multi-step workflow, or a community layer (shared AI results, collaborative features). These additions make the app clearly native rather than a web-equivalent.

  Review the configuration in src/ or app/ directory for implementation patterns.