Best-practices guide for react-native-vision-camera v5 (Nitro rewrite, April 2026) and migrating from v4. Use when installing, configuring, or writing code with the Camera, outputs, frame processors, recording, or barcode/depth/RAW features. Also use when converting v4 code (photo={true}, takePhoto, useCameraFormat, useFrameProcessor) to the new v5 API.
npx skills add https://github.com/margelo/react-native-skills --skill react-native-vision-camera
VisionCamera v5 is the maintained and latest version of react-native-vision-camera. It is a full Nitro Modules rewrite with a new Constraints API, Output-based architecture, in-memory Photo, and a hard break from the v4 format/prop model. Almost every v4 surface is gone or renamed — treat v5 as a new API, not an incremental upgrade.
This skill is a router. Read this file first, then load the reference that matches the task. Every reference is self-contained — do not load more than you need.
When in doubt, load references/migration-v4-to-v5.md — it covers the shape of the new API by contrasting it with v4 and is the fastest orientation.
These are the rules that catch people who "know" v4. Apply them without asking:
react-native-nitro-modules and react-native-nitro-image are required peer deps. Frame processors additionally require react-native-vision-camera-worklets AND react-native-worklets (Software Mansion's — not -core). Worklets - https://docs.swmansion.com/react-native-worklets/docs/outputs={[...]} replaces photo / video / frameProcessor / codeScanner props. Create outputs with usePhotoOutput, useVideoOutput, useFrameOutput, useDepthOutput, useObjectOutput (or useBarcodeScannerOutput from the barcode package) and pass them in an array. Capture methods (capturePhoto, createRecorder) live on the Output, not the Camera ref.format prop and no useCameraFormat. Use constraints={[...]} — array order = priority, descending. The Camera negotiates the closest supported config automatically, so an impossible constraint like { fps: 99999 } never throws.takePhoto() does not exist. Use photoOutput.capturePhoto(settings, callbacks) for in-memory Photo, or photoOutput.capturePhotoToFile(...) for a file path. The default path is in-memory — do not write temp files unless explicitly asked.FrameProcessorPlugin base class, VISION_EXPORT_SWIFT_FRAME_PROCESSOR macro, and VisionCameraProxy.addFrameProcessorPlugin are gone. A v5 plugin is a HybridObject with a typed Nitro spec. See references/frame-processors.md.Frame (and Depth) MUST be .dispose()d. The buffer pool is bounded; leaking a frame stalls the pipeline. Wrap work in try { ... } finally { frame.dispose() }. When offloading via asyncRunner.runAsync(...), dispose inside the async callback if it returned true, and dispose immediately in the else branch when it returned false.react-native-vision-camera-barcode-scanner is a separate package, MLKit-based on both platforms. For iOS-only object detection (QR, faces, bodies via native AVFoundation metadata, no ML dep), use useObjectOutput from core.isActive. Remounting tears down the session. Integrate with useIsFocused() from react-navigation so the session goes Idle → Ready while not on screen, and keeps preferences warm for fast resume.pixelFormat defaults to 'native' (zero-copy), NOT 'yuv'. 'native' streams in the session's negotiated nativePixelFormat with zero conversions (it may resolve to a YUV, RGB, RAW, or 'private' format — verify the actual one via frame.pixelFormat). 'yuv' picks the YUV format closest to native and is the best general-purpose CPU-accessible choice (MLKit/OpenCV/Skia); 'rgb' forces a YUV→RGB conversion (~2.6× more bandwidth) — use only when a consumer hard-requires RGB. useDepthOutput has no pixelFormat option. For ML, prefer react-native-vision-camera-resizer (GPU) over paying a per-frame RGB conversion in the camera pipeline.<!-- source: useFrameOutput.ts:123 (pixelFormat = 'native' default); VideoPixelFormat.ts:52-62; CameraFrameOutput.nitro.ts:71,84-86 ("recommended to use 'native' ... zero-copy GPU-only path"); useDepthOutput.ts:70-77 (options have no pixelFormat) -->
10. Do not hand-clamp FPS/resolution with Math.min/Math.max. That was a v4 workaround. In v5 the Constraints API negotiates internally — express intent and let the Camera pick.
11. Worklets mutate Reanimated SharedValues directly in v5. The worklets-core bridge is gone; no runOnJS round-trip required to update a Reanimated SharedValue from a frame processor.
useCameraPermission + useCameraDevice + usePhotoOutput + <Camera />). Use the imperative VisionCamera.createCameraSession(...) API only when the user asks for multi-cam or full programmatic control.react-native-vision-camera-resizer (GPU-accelerated, returns a pooled GPUFrame) over vision-camera-resize-plugin (v4-era, CPU).<!-- source: react-native-vision-camera-resizer/src/specs/GPUFrame.nitro.ts + Resizer.nitro.ts (GPU resize→GPUFrame). The often-quoted "~5×" figure is a blog claim, not in source, so it is omitted here. -->
react-native-nitro-modules, react-native-nitro-image, or (for frame processors) react-native-worklets + react-native-vision-camera-worklets.llms.txt index: https://visioncamera.margelo.com/llms.txtgh api repos/mrousavy/react-native-vision-camera/releases/tags/v5.0.0Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take margelo/react-native-vision-camera from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.