axiom-ios-ai

charleswiltgen/axiom · updated Apr 8, 2026

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$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-ios-ai
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summary

You MUST use this skill for ANY Apple Intelligence or Foundation Models work.

skill.md

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)

how to use axiom-ios-ai

How to use axiom-ios-ai on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add axiom-ios-ai
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-ios-ai

The skills CLI fetches axiom-ios-ai from GitHub repository charleswiltgen/axiom and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/axiom-ios-ai

Reload or restart Cursor to activate axiom-ios-ai. Access the skill through slash commands (e.g., /axiom-ios-ai) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.651 reviews
  • Dhruvi Jain· Dec 28, 2024

    axiom-ios-ai reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ren Perez· Dec 28, 2024

    We added axiom-ios-ai from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Michael Rao· Dec 16, 2024

    axiom-ios-ai is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Mei Ghosh· Dec 16, 2024

    Keeps context tight: axiom-ios-ai is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Pratham Ware· Dec 8, 2024

    Solid pick for teams standardizing on skills: axiom-ios-ai is focused, and the summary matches what you get after install.

  • Oshnikdeep· Nov 19, 2024

    I recommend axiom-ios-ai for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakura Lopez· Nov 19, 2024

    Keeps context tight: axiom-ios-ai is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Sofia Flores· Nov 7, 2024

    axiom-ios-ai fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ren Diallo· Nov 7, 2024

    We added axiom-ios-ai from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ren Lopez· Oct 26, 2024

    We added axiom-ios-ai from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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