Core Ml

This handles the full spectrum of on-device machine learning for Apple platforms, from integrating pre-trained Core ML models to using Vision for OCR and object detection or NaturalLanguage for sentiment analysis. The decision guide upfront is smart: it walks you through whether you actually need Core ML versus Apple's newer Foundation Models, or if a built-in Vision or NaturalLanguage request will do the job without a custom model. Covers real-time camera integration, Create ML training workflows, and model optimization techniques like quantization. If you're adding image classification, sound analysis, or custom predictions to an iOS or macOS app, this gets you from zero to working inference code with proper error handling and performance tuning.

skills.sh installs: 427
GitHub stars: 879
last updated: Aug 21, 2026

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Install

$ npx -y skills add rshankras/claude-code-apple-skills --skill core-ml --agent claude-code

Installs into .claude/skills of the current project.

Files

Core ML Skills

Combined advisory, generator, and workflow skill for integrating machine learning into Apple platform apps. Covers Core ML model integration, Vision framework image analysis, NaturalLanguage framework text processing, Create ML training, and on-device model optimization.

When This Skill Activates

Use this skill when the user:

Wants to add ML capabilities to their app
Needs to integrate a Core ML model (.mlmodel) into an Xcode project
Wants to use the Vision framework for image analysis (faces, text recognition, body pose, object detection)
Wants to use the NaturalLanguage framework for text processing (sentiment, entities, language detection)
Needs to train a custom model with Create ML
Wants to optimize a model for on-device use (quantization, pruning, palettization)
Needs to choose between Core ML and Foundation Models (Apple Intelligence)
Asks about image classification, object detection, sound classification, or tabular data prediction
Wants real-time camera + ML processing