「dynamic」の検索結果

Implement AlarmKit alarms and countdown timers for iOS and iPadOS with Lock Screen, Dynamic Island, StandBy, and paired Apple Watch system UI. Covers AlarmManager scheduling, AlarmAttributes and AlarmPresentation, system Stop and AlarmButton secondary actions, authorization, state observation, countdown widget-extension handoff, and Live Activity integration. Use when building wake-up alarms, countdown timers, or alarm-style alerts that need Apple's system alarm experience.

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Build and audit SwiftUI, UIKit, and AppKit accessibility for VoiceOver, Voice Control, Switch Control, Full Keyboard Access, Dynamic Type, focus restoration, labels/traits/actions, traversal, custom rotors, NSAccessibility, XCTest checks, adaptive system preferences, and App Store accessibility declarations. Use when implementing accessible UI, fixing an accessibility audit, testing assistive-technology behavior, or substantiating App Store Accessibility Nutrition Labels.

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, review, or improve localization and internationalization in iOS/macOS apps — String Catalogs (.xcstrings), generated localizable symbols, stable key naming, LocalizedStringKey, LocalizedStringResource, pluralization, FormatStyle for numbers/dates/measurements, right-to-left layout, Dynamic Type, and locale-aware formatting. Use when adding multi-language support, setting up String Catalogs, enabling generated symbols for compile-time-safe localization keys, handling plural forms, formatting dates/numbers/currencies for different locales, testing localizations, or making UI work correctly in RTL languages like Arabic and Hebrew.

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Generate GNSS baseband waveforms (GPS, Galileo, NavIC) with physically realistic or user-specified channel impairments using the Satellite Communications Toolbox. Use when generating GPS L1 C/A, L1C, L2C, L5, Galileo E1, E1C, E5a, E5b, E5, or NavIC L5, S, L1 signals. Covers gpsWaveformGenerator, galileoWaveformGenerator, satelliteScenario, Doppler/delay from orbital dynamics or custom values, navigation data encoding with ephemeris, and RINEX integration. Triggers on: GPS waveform, Galileo waveform, NavIC waveform, GNSS signal, satellite scenario, GNSS simulation, receiver test signal, baseband GNSS, L-band satellite signal, navigation signal generation.

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。

Design and implement real-time audio processing chains using Audio Toolbox streaming objects. Use when building frame-based audio processing loops, multiband filters, dynamic range control, parametric EQ, level metering, loudness metering, SPL metering, octave-band analysis, sample rate conversion, frequency-domain filtering (long impulse responses, custom filter banks), or audio chains in Simulink. Covers visualization (visualize method), interactive tuning (parameterTuner), MIDI control, and Audio Toolbox Simulink blocks. Use when the user says "real-time audio", "streaming audio", "audio filter", "compressor", "equalizer", "level meter", "loudness meter", "SPL meter", "octave bands", "crossover filter", "audio chain", "MIDI control", "convolution reverb", "impulse response streaming", "frequency-domain filter", or asks to process audio frame-by-frame.

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。

Deploy MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression.

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 C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. Use when the user wants to integrate an AI model into an application with code generation as the end goal — generating MEX, CUDA MEX, static library, dynamic library, or executable — or using the model in Simulink for simulation and code generation. Covers PyTorch ExportedProgram (.pt2) via loadPyTorchExportedProgram and LiteRT (.tflite) via loadLiteRTModel (R2026a+). Keywords: PyTorch, torch, .pt2, ExportedProgram, loadPyTorchExportedProgram, invoke, codegen, MEX, CUDA, GPU, C, C++, deploy, AI model, deep learning model, LiteRT, TFLite, TensorFlow Lite, Simulink, slbuild, PyTorch ExportedProgram block, MATLAB Function block, dlosslib, loadLiteRTModel.

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Identify a linear dynamic model from input-output or time-series data using MATLAB System Identification Toolbox. Use when estimating transfer function, state-space, ARX, ARMAX, BJ, OE polynomial or process models from measurement 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。

Generate, verify, refine, and accelerate C/C++ or CUDA code from MATLAB with MATLAB Coder, Embedded Coder, GPU Coder, or MATLAB Test. Also covers writing codegen-ready MATLAB code: language constraints, coder.* directives, and optimization patterns. Triggers on: codegen, MEX, deploy MATLAB as C/C++, GPU Coder, coder.screener, coder.config, coder.gpuConfig, coder.typeof, coder.runTest, matlabtest.coder.TestCase, SIL, embedded config, no dynamic memory, EnableMexProfiling, coder.timeit, coder.perfCompare, %#codegen, writing codegen-ready MATLAB, code generation readiness, coder.varsize, coder.unroll, coder.noImplicitExpansionInFunction, coder.ceval, coder.inline, coder.extrinsic, coder.const, coder.classSignature, class codegen limitations, temporal types codegen, DMA-off, stack-only, host-target InstructionSetExtensions, SIMDAcceleration, OptimizeReductions, host SIMD tuning, host OpenMP, codegen performance.

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 secrets and PKI with HashiCorp Vault. Configure secret engines, authentication methods, and policies. Use when implementing centralized secrets management, dynamic credentials, or certificate management.

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。

Perform dynamic application security testing with OWASP ZAP, Burp Suite, and Nikto. Test running applications for security vulnerabilities through automated and manual testing. Use when testing web applications, APIs, or performing penetration testing.

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。

Design personalization strategies for e-commerce stores. Product recommendations, dynamic content, customer segmentation, and personalized email/SMS based on browsing and purchase behavior.

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。

Backend plugin architecture, DeviceInterface, dynamic loading, and command encoding.

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。

Physics-based animation library combining React Spring (spring dynamics, gesture integration, 60fps animations) and Popmotion (low-level composable animation utilities, reactive streams). Use when building fluid, natural-feeling UI animations, gesture-driven interfaces, physics simulations, or spring-loaded interactions. Triggers on tasks involving React Spring hooks, spring physics, inertia scrolling, physics-based motion, animation composition, or natural UI movements. Alternative physics approach to motion-framer for more physically accurate animations.

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。

When the user wants to optimize URL structure, fix URL issues, or plan URL hierarchy. Also use when the user mentions "URL structure," "URL optimization," "slug," "clean URLs," "URL hierarchy," "URL path," "permalink structure," "URL best practices," "dynamic URLs," or "URL parameters." For per-page slug wording, use url-slug-generator. For canonical consolidation, use canonical-tag.

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。

When the user wants to choose or optimize rendering strategy for SEO. Also use when the user mentions "SSR," "SSG," "CSR," "ISR," "static rendering," "dynamic rendering," "server-side rendering," "client-side rendering," "JavaScript rendering," "pre-rendering," "prerender," "content in initial HTML," or "crawler visibility." For crawl issues, use site-crawlability.

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。

Use when an Unreal Engine 5.8 project misses its frame rate or stutters: "optimize to 60 fps", "we run at 38 fps", CPU or GPU bound, game or render thread too long, hitches, traversal or shader stutter (PSO), GC spikes, camera-cut spikes, Lumen, Nanite, VSM, ray tracing, foliage, crowds or Niagara too expensive, async compute, stat unit, ProfileGPU, Unreal Insights, TraceQuery, snapshothitches, scalability and device profiles, dynamic resolution and TSR, streaming budgets, or proving a fix with before and after captures.

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。

Use when sculpting a realistic head, face, portrait, body or creature in ZBrush (anatomy, landmarks, proportions, "the face looks off", eyes, lips, jaw), adding skin, pores, wrinkles or reptile and dragon scales with alphas, Surface Noise, layers or morph targets, planning subdivision or HD Geometry for a film close-up, reprojecting detail, sculpting cloth folds or running Dynamics cloth, growing FiberMesh fur or hair, making horns, or judging a character sculpt the way a senior character artist would.

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。

Use when modeling hard surface in ZBrush 2026 (sci-fi helmet, weapon, prop, armor plates, mechanical parts, kitbash, vents, panel lines, bolts, concept to game asset), when using ZModeler, Dynamic Subdivision and creasing, Live Boolean, Knife, Clip, Slice or Trim curves, IMM, ArrayMesh, NanoMesh or Panel Loops, or when edges look razor sharp, a Make Boolean Mesh fails or leaves holes, planes look wobbly, Mirror And Weld erased an edit, or ZRemesher ruins a hard-surface part.

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。

Use when an agent sculpts organic forms in ZBrush 2026 (sculpt a head, bust or creature in ZBrush from a sphere, ZSpheres or primitives); when blocking primary and secondary forms, choosing DynaMesh, Sculptris Pro or subdivision levels, or setting ClayBuildup, Dam_Standard, Move or TrimDynamic; when using masks, polygroups, Morph Targets or layers; or when scripted strokes miss, do nothing, come out too strong or leave marks, or a re-DynaMesh does nothing or loses polygroups.

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。

Run upstream brand discovery covering audience research, competitive landscape, category dynamics, problem space, and positioning territory exploration. Use this skill at the very start of a brand or website project when the user needs to understand who they're for, who they compete with, what the audience actually needs, and where the brand could plausibly stand. Triggers on brand discovery, audience research, market research, competitive scan, category research, customer research, who is this for, who are we, positioning research, intake, kickoff. Also triggers when a creative brief is requested but the upstream inputs (audience, competitors, problem space) are not yet clear.

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。

Verify a ForgeCAD MJCF export in MuJoCo with dynamics, contacts, controls, joint travel, and rendered evidence before calling it simulation-ready.

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。

Example skill loaded from resources_discover

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。

Computational fluid dynamics simulation and analysis

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。