Can this skill help with UI freezes during AI generation?

Yes, it helps identify when model calls are being made on the main thread and provides the correct asynchronous Task {} patterns to keep the interface responsive.

How do I handle guardrail violations in my app?

The skill provides a pattern to catch LanguageModelSession.GenerationError.guardrailViolation and suggest user-friendly UI responses instead of app crashes.

Why does my model generation work in the simulator but not on a physical device?

This usually indicates the physical device is not Apple Intelligence-capable, the region is restricted, or the user has not opted in. The skill includes automated checks for these specific scenarios.

What is the token limit for Apple Foundation Models?

The default limit is approximately 4,096 tokens for input and output combined. This skill helps you monitor usage and provides patterns for condensing transcripts when this limit is reached.

Foundation Models Diagnostics

Name: Foundation Models Diagnostics
Author: CharlesWiltgen

byCharlesWiltgen

•

233

Mobile Development

Diagnoses and resolves issues with Apple Intelligence Foundation Models, including context limits, guardrail violations, and availability errors.

关于

This skill provides a systematic diagnostic framework for troubleshooting Apple’s on-device Foundation Models across iOS, macOS, and other Apple platforms. It helps developers identify whether issues stem from device-scale model limitations (like the 3B parameter 4096-token constraint), regional unavailability, or implementation errors such as main-thread blocking. By offering structured patterns for handling context window exhaustion, guardrail violations, and performance bottlenecks, it ensures robust integration of Apple Intelligence features in modern xOS applications.

主要功能

233 GitHub stars
Context window and token usage estimation (4096-token limit)
Guardrail violation and content policy diagnostic patterns
Systematic availability and regional support verification
Transcript inspection to debug hallucinations and output quality
Performance profiling for model generation latency

使用场景

Optimizing UI responsiveness by identifying main-thread blocking during AI tasks
Verifying device compatibility and user opt-in status for Apple Intelligence
Debugging exceededContextWindowSize errors in long conversational interfaces

关于

主要功能

233 GitHub stars
Context window and token usage estimation (4096-token limit)
Guardrail violation and content policy diagnostic patterns
Systematic availability and regional support verification
Transcript inspection to debug hallucinations and output quality
Performance profiling for model generation latency

使用场景

Optimizing UI responsiveness by identifying main-thread blocking during AI tasks
Verifying device compatibility and user opt-in status for Apple Intelligence
Debugging exceededContextWindowSize errors in long conversational interfaces