iOS Apple Intelligence Router
You MUST use this skill for ANY Apple Intelligence or Foundation Models work.
When to Use
Use this router when:
- Implementing Apple Intelligence features
- Using Foundation Models
- Working with LanguageModelSession
- Generating structured output with @Generable
- Debugging AI generation issues
- iOS 26 on-device AI
AI Approach Triage
First, determine which kind of AI the developer needs:
| Developer Intent |
Route To |
| On-device text generation (Apple Intelligence) |
Stay here → Foundation Models skills |
| Custom ML model deployment (PyTorch, TensorFlow) |
Route to ios-ml → CoreML conversion, compression |
| Computer vision (image analysis, OCR, segmentation) |
Route to ios-vision → Vision framework |
| Cloud API integration (OpenAI, etc.) |
Route to ios-networking → URLSession patterns |
| System AI features (Writing Tools, Genmoji) |
No custom code needed — these are system-provided |
Key boundary: ios-ai vs ios-ml
- ios-ai = Apple's Foundation Models framework (LanguageModelSession, @Generable, on-device LLM)
- ios-ml = Custom model deployment (CoreML conversion, quantization, MLTensor, speech-to-text)
- If developer says "run my own model" → ios-ml. If "use Apple Intelligence" → ios-ai.
Cross-Domain Routing
Foundation Models + concurrency (session blocking main thread, UI freezes):
- Foundation Models sessions are async — blocking likely means missing
await or running on @MainActor
- Fix here first using async session patterns in foundation-models skill
- If concurrency issue is broader than Foundation Models → also invoke ios-concurrency
Foundation Models + data (@Generable decoding errors, structured output issues):
- @Generable output problems are Foundation Models-specific, NOT generic Codable issues
- Stay here → foundation-models-diag handles structured output debugging
- If developer also has general Codable/serialization questions → also invoke ios-data
Routing Logic
Foundation Models Work
Implementation patterns → /skill axiom-foundation-models
- LanguageModelSession basics
- @Generable structured output
- Tool protocol integration
- Streaming with PartiallyGenerated
- Dynamic schemas
- 26 WWDC code examples
API reference → /skill axiom-foundation-models-ref
- Complete API documentation
- All @Generable examples
- Tool protocol patterns
- Streaming generation patterns
Diagnostics → /skill axiom-foundation-models-diag
- AI response blocked
- Generation slow
- Guardrail violations
- Context limits exceeded
- Model unavailable
Decision Tree
- Custom ML model / CoreML / PyTorch conversion? → Route to ios-ml (not this router)
- Computer vision / image analysis / OCR? → Route to ios-vision (not this router)
- Cloud AI API integration? → Route to ios-networking (not this router)
- Implementing Foundation Models / @Generable / Tool protocol? → foundation-models
- Need API reference / code examples? → foundation-models-ref
- Debugging AI issues (blocked, slow, guardrails)? → foundation-models-diag
- Foundation Models + UI freezing? → foundation-models (async patterns) + also invoke ios-concurrency if needed
Anti-Rationalization
| Thought |
Reality |
| "Foundation Models is just LanguageModelSession" |
Foundation Models has @Generable, Tool protocol, streaming, and guardrails. foundation-models covers all. |
| "I'll figure out the AI patterns as I go" |
AI APIs have specific error handling and fallback requirements. foundation-models prevents runtime failures. |
| "I've used LLMs before, this is similar" |
Apple's on-device models have unique constraints (guardrails, context limits). foundation-models is Apple-specific. |
Critical Patterns
foundation-models:
- LanguageModelSession setup
- @Generable for structured output
- Tool protocol for function calling
- Streaming generation
- Dynamic schema evolution
foundation-models-diag:
- Blocked response handling
- Performance optimization
- Guardrail violations
- Context management
Example Invocations
User: "How do I use Apple Intelligence to generate structured data?"
→ Invoke: /skill axiom-foundation-models
User: "My AI generation is being blocked"
→ Invoke: /skill axiom-foundation-models-diag
User: "Show me @Generable examples"
→ Invoke: /skill axiom-foundation-models-ref
User: "Implement streaming AI generation"
→ Invoke: /skill axiom-foundation-models
User: "I want to add AI to my app"
→ First ask: Apple Intelligence (Foundation Models) or custom ML model? Route accordingly.
User: "My Foundation Models session is blocking the UI"
→ Invoke: /skill axiom-foundation-models (async patterns) + also invoke ios-concurrency if needed
User: "I want to run my PyTorch model on device"
→ Route to: ios-ml router (CoreML conversion, not Foundation Models)
