Agent-Skills.md

Agent Skills: iOS Apple Intelligence Router

Use when implementing ANY Apple Intelligence or on-device AI feature. Covers Foundation Models, @Generable, LanguageModelSession, structured output, Tool protocol, iOS 26 AI integration.

UncategorizedID: charleswiltgen/axiom/axiom-ios-ai

Repository

charleswiltgen/axiom
CharlesWiltgenLicense: MIT
42644

Install this agent skill to your local

pnpm dlx add-skill https://github.com/CharlesWiltgen/Axiom/tree/HEAD/.claude-plugin/plugins/axiom/skills/axiom-ios-ai

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.claude-plugin/plugins/axiom/skills/axiom-ios-ai/SKILL.md

Skill Metadata

Name
axiom-ios-ai
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.

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

  1. Custom ML model / CoreML / PyTorch conversion? → Route to ios-ml (not this router)
  2. Computer vision / image analysis / OCR? → Route to ios-vision (not this router)
  3. Cloud AI API integration? → Route to ios-networking (not this router)
  4. Implementing Foundation Models / @Generable / Tool protocol? → foundation-models
  5. Need API reference / code examples? → foundation-models-ref
  6. Debugging AI issues (blocked, slow, guardrails)? → foundation-models-diag
  7. 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)