apple-intelligence
Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, and intelligent assistants. Use when implementing AI-powered features.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install rshankras-claude-code-apple-skills-apple-intelligence
Repository
Skill path: skills/apple-intelligence
Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, and intelligent assistants. Use when implementing AI-powered features.
Open repositoryBest for
Primary workflow: Design Product.
Technical facets: Full Stack, Data / AI, Designer.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: rshankras.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install apple-intelligence into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/rshankras/claude-code-apple-skills before adding apple-intelligence to shared team environments
- Use apple-intelligence for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: apple-intelligence description: Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, and intelligent assistants. Use when implementing AI-powered features. allowed-tools: [Read, Write, Edit, Glob, Grep, Bash, AskUserQuestion] --- # Apple Intelligence Skills Skills for implementing Apple Intelligence features including on-device LLMs, visual recognition, and intelligent assistants. ## When This Skill Activates Use this skill when the user: - Wants to add AI/LLM features to their app - Needs on-device text generation or understanding - Asks about Foundation Models or Apple Intelligence - Wants to implement structured AI output - Needs prompt engineering guidance - Wants camera-based visual intelligence features ## Available Skills ### foundation-models/ On-device LLM integration with prompt engineering best practices. - Model availability checking - Session management - @Generable structured output - Tool calling patterns - Snapshot streaming - Prompt engineering techniques ### visual-intelligence/ Integrate with iOS Visual Intelligence for camera-based search. - IntentValueQuery implementation - SemanticContentDescriptor handling - AppEntity for searchable content - Display representations - Deep linking from results ## Key Principles ### 1. Privacy First - All processing happens on-device - No cloud connectivity required - User data never leaves the device ### 2. Graceful Degradation - Always check model availability - Provide fallback UI for unsupported devices - Handle errors gracefully ### 3. Efficient Prompting - Keep prompts focused and specific - Use structured output when possible - Respect context window limits (4,096 tokens) ## Reference Documentation - `/Users/ravishankar/Downloads/docs/FoundationModels-Using-on-device-LLM-in-your-app.md` - `/Users/ravishankar/Downloads/docs/Implementing-Visual-Intelligence-in-iOS.md`