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callstackincubator/ai72 installs

react-native-ai-skills

Provides integration recipes for the React Native AI @react-native-ai packages that wrap the Llama.rn (Llama.cpp), MLC-LLM, Apple Foundation backends. Use when integrating local on-device AI in React Native, setting up providers, model management.

How do I install this agent skill?

npx skills add https://github.com/callstackincubator/ai --skill react-native-ai-skills
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill provides integration recipes for on-device AI in React Native using the @react-native-ai ecosystem. It includes instructions for Apple Intelligence, GGUF models (via llama.rn), MLC-LLM, and NCNN. All external resources, packages, and documentation links are consistent with the vendor's own infrastructure (Callstack/callstackincubator).

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • Runlayerwarn

    3/6 files flagged

What does this agent skill do?

React Native AI Skills

Overview

Example workflow for integrating on-device AI in React Native apps using the @react-native-ai ecosystem. Available provider tracks (can be combined):

  • Apple – Apple Intelligence (iOS 26+)
  • Llama – GGUF models via llama.rn
  • MLC – MLC-LLM models
  • NCNN – Low-level NCNN inference wrapper (vision, custom models)

Path Selection Gate (Must Run First)

Before selecting any reference file, classify the user request:

  1. Select Apple:
    • if you intend to build with: apple, Apple Intelligence, Apple Foundation Models
    • if you want features: transcription, speech synthesis, embeddings on Apple devices
    • optionally with capabilities: tool calling
  2. Select Llama:
    • if you intend to use the following technologies: llama, GGUF, llama.rn, HuggingFace, SmolLM
    • if you want to perform the following operations: embedding model, rerank, speech model
  3. Select MLC:
    • if you intend to use a library that allows for custom models and involves build-time model optimizations
  4. Select NCNN:
    • if you need to use run low-level inference on bare metal tensors
    • if you intend to run inference of custom models such as convolutional networks, multi-layer perceptrons, low-level inference, etc.
    • DO NOT select NCNN if the prompt mentions LLMs only, this use case is better solved by other providers

Skill Format

Each reference file follows a strict execution format:

  • Quick Command
  • When to Use
  • Prerequisites
  • Step-by-Step Instructions
  • Common Pitfalls
  • Related Skills

Use the checklists exactly as written before moving to the next phase.

When to Apply

Reference this package when:

  • Integrating on-device AI in React Native apps
  • Installing and configuring @react-native-ai providers
  • Managing model downloads (llama, mlc)
  • Wiring providers with Vercel AI SDK (generateText, streamText)
  • Implementing SetupAdapter pattern for multi-provider apps
  • Debugging native module or Expo plugin issues

Priority-Ordered Guidelines

PriorityCategoryImpactStart File
1Path selection and baselineN/Aquick-start
2Apple providerN/Aapple-provider
3Llama providerN/Allama-provider
4MLC-LLM providerN/Amlc-provider
5NCNN providerN/Ancnn-provider

Quick Reference

npm install

# Provider-specific install
npm add @react-native-ai/apple
npm add @react-native-ai/llama llama.rn
npm add @react-native-ai/mlc
npm add @react-native-ai/ncnn-wrapper

Route by path:

References

FileImpactDescription
quick-startN/AShared preflight
apple-providerN/AApple Intelligence setup and integration
llama-providerN/AGGUF models, llama.rn, model management
mlc-providerN/AMLC models, download, prepare, Expo plugin
ncnn-providerN/ANCNN wrapper, loadModel, runInference

Problem → Skill Mapping

ProblemStart With
Need path decision firstquick-start
Integrate Apple Intelligenceapple-provider
Run GGUF models from HuggingFacellama-provider
Run MLC-LLM models (Llama, Phi, Qwen)mlc-provider
Use NCNN for custom inferencencnn-provider
Multi-provider app with SetupAdapterquick-start → provider-specific
Expo + native module setupProvider-specific (each has Expo notes)

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

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