1,582 件 ・ 関連度順
概要と使いどころ
Use when working with HealthKit, WorkoutKit, health data, workouts, or fitness features on iOS or watchOS. Covers permissions, queries, background delivery, custom workouts, multidevice coordination.
日本語の概要は準備中です。原文の説明を表示しています。
Apply modern Swift language patterns and idioms for non-concurrency, non-SwiftUI code. Covers if/switch expressions (Swift 5.9+), typed throws (Swift 6+), result builders, property wrappers, opaque and existential types (some vs any), guard patterns, Never type, Regex builders (Swift 5.7+), basic Codable shaping (CodingKeys, custom decoding, nested containers), modern collection APIs (count(where:), contains(where:), replacing()), basic FormatStyle usage, and string interpolation patterns. Use when writing core Swift code involving generics, protocols, enums, closures, or modern language features; route deep Codable to swift-codable, detailed formatting/localization to swift-formatstyle, and API naming to swift-api-design-guidelines.
日本語の概要は準備中です。原文の説明を表示しています。
Implement computer vision features including text recognition (OCR), face detection, barcode scanning, image segmentation, object tracking, and document scanning in iOS apps. Covers both the modern Swift-native Vision API (iOS 18+) and legacy VNRequest patterns, VisionKit DataScannerViewController for live camera scanning, and CoreMLRequest/VNCoreMLRequest for custom model inference. Use when adding OCR, barcode scanning, face detection, or custom Core ML model inference with Vision.
日本語の概要は準備中です。原文の説明を表示しています。
Build shared real-time experiences using GroupActivities and SharePlay. Use when implementing shared media playback, collaborative app features, synchronized game state, or any FaceTime, Messages, AirDrop, or nearby visionOS group activity on iOS, macOS, tvOS, or visionOS.
日本語の概要は準備中です。原文の説明を表示しています。
Add Apple Pencil drawing with PKCanvasView, PKToolPicker, PKDrawing serialization/export, stroke inspection, and PencilKit/PaperKit handoffs. Use when building drawing apps, annotation features, handwriting capture, signature fields, content-version-safe ink workflows, or Apple Pencil-powered experiences on iOS/iPadOS/visionOS.
日本語の概要は準備中です。原文の説明を表示しています。
Add drawings, shapes, and a consistent markup experience using PaperKit. Use when integrating PaperMarkupViewController for markup editing, adding shape recognition, working with PaperMarkup data models, embedding markup tools in document editors, or building annotation features that need the system-standard markup toolbar. New in iOS 26.
日本語の概要は準備中です。原文の説明を表示しています。
Build private, on-device AI features on iPhone, iPad, and Mac with Foundation Models, Core ML, MLX Swift, or llama.cpp. Use when choosing an Apple-local model runtime, building an Apple Intelligence chatbot or tool-calling feature, running an LLM on Apple Silicon, converting or compressing a Python model for Core ML, or comparing on-device inference backends. For Swift Core ML loading and prediction code, use the coreml skill.
日本語の概要は準備中です。原文の説明を表示しています。
Integrate Game Center features using GameKit. Use when authenticating GKLocalPlayer, checking player restrictions, submitting leaderboard scores, reporting achievements, implementing real-time or turn-based matchmaking, handling GKMatch data, showing the Game Center dashboard or access point, adding challenges and friend invitations, saving game data, or verifying player identity on a server.
日本語の概要は準備中です。原文の説明を表示しています。
Access Core Motion accelerometer, gyroscope, magnetometer, device-motion, pedometer, activity-recognition, altitude, headphone motion, batched high-frequency workout motion, and water-submersion/depth data. Use when reading device sensors, counting steps, detecting walking/running/driving/cycling, tracking altitude, building motion interactions, handling AirPods head tracking, or implementing watchOS dive/depth features.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze signal spectra in MATLAB using nonparametric and parametric estimators. Use when computing frequency content, PSD, power spectrum, spectral peaks, bandwidth, or streaming spectral analysis. Covers pspectrum, pwelch, periodogram, pmtm, pburg, pmusic, rootmusic, plomb, poctave, spectrumAnalyzer, dsp.SpectrumEstimator. TRIGGER: FFT, PSD, power spectrum, spectral analysis, frequency content, bandwidth measurement, spectral leakage, window selection, streaming spectrum, periodicity, resolve close frequencies, multitaper. DO NOT TRIGGER: filter design, spectrogram/time-frequency, audio features.
日本語の概要は準備中です。原文の説明を表示しています。
Generate and structure MATLAB unit tests using matlab.unittest and matlab.uitest features, including class-based tests, parameterized testing, fixtures, mocking, and app testing with gestures. Use when writing, generating, or adding tests, creating test classes, adding test methods, parameterizing tests, setting up fixtures, mocking dependencies, or testing App Designer apps. Do NOT use for running tests, collecting coverage, or CI/CD configuration.
日本語の概要は準備中です。原文の説明を表示しています。
Interpret and explain a trained tabular machine-learning model (classification or regression) in MATLAB. Find which predictors, features, or columns matter most; explain why the model made a specific prediction, including diagnosing predictions it got wrong; show how a predictor affects the output; and compare how the model behaves across cohorts or subgroups. Uses model-agnostic techniques and model-native measures, and works on custom models (such as a dlnetwork) through a prediction function handle. Use for model interpretability, explainability, and feature-importance questions on tabular data, not for training, tuning, feature selection, deploying models, or models trained on image, text, signal, or other non-tabular data.
日本語の概要は準備中です。原文の説明を表示しています。
Read, write, and manipulate medical imaging data (DICOM, NIfTI, NRRD) in MATLAB. Covers Image Processing Toolbox functions (dicomreadVolume, niftiread, dicomContours, dicomanon) and Medical Imaging Toolbox enhanced APIs (medicalVolume, medicalImage, medicalref3d, extractSlice, updateOrientation). Use when reading medical files, listing DICOM series, extracting spatial referencing, changing orientation, working with RT structures, or anonymizing DICOM data. Some features require Medical Imaging Toolbox — see skill body and references for details.
日本語の概要は準備中です。原文の説明を表示しています。
Apply CIS benchmarks and secure Linux servers. Configure SSH, manage users, implement firewall rules, and enable security features. Use when hardening Linux systems for production or meeting security compliance requirements.
日本語の概要は準備中です。原文の説明を表示しています。
Harden Windows servers per security baselines and CIS benchmarks. Configure Group Policy, Windows Defender, and security features. Use when securing Windows Server environments.
日本語の概要は準備中です。原文の説明を表示しています。
Manage Red Hat OpenShift clusters and deployments. Configure projects, routes, builds, and deploy applications using OpenShift-specific features. Use when working with OpenShift Container Platform or OKD for enterprise Kubernetes.
日本語の概要は準備中です。原文の説明を表示しています。
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
日本語の概要は準備中です。原文の説明を表示しています。
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
日本語の概要は準備中です。原文の説明を表示しています。
Search library/framework documentation via llms.txt (context7.com). Use for API docs, GitHub repository analysis, technical documentation lookup, latest library features.
日本語の概要は準備中です。原文の説明を表示しています。
Discover related plans for the current task: same feature folder full depth, other features active-only, general-plans active. Like vc-context-discovery but for plan artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.
日本語の概要は準備中です。原文の説明を表示しています。
Generate comprehensive edge cases and test scenarios by decomposing features across 12 dimensions. Use before implementation or testing to catch issues early.
日本語の概要は準備中です。原文の説明を表示しています。
MANDATORY for every coding agent (Claude Code, Codex, or any other) — keep this repository's documentation in sync after any change to behavior, configuration, interfaces, events, schema, or features. Use automatically at the end of change-sets that alter an env var, event type, hook or state behavior, API, schema, WebSocket message, MCP tool, CLI command, or user-facing feature, and whenever the user asks to update documentation.
日本語の概要は準備中です。原文の説明を表示しています。
Generate a complete, deployable landing page from a brief. Produces a single self-contained HTML file with Tailwind CSS (via CDN), responsive design, dark mode, semantic HTML, and OG meta tags. Sections: hero with CTA, features, social proof, pricing (optional), FAQ, footer. Use when building a marketing page, product launch page, coming soon page, or any standalone landing page. Triggers: 'landing page', 'create a page', 'marketing page', 'launch page', 'coming soon page', 'one-page site'.
日本語の概要は準備中です。原文の説明を表示しています。