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