「device」の検索結果

Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.

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。

Document control for medical device QMS, covering numbering, version control, change management, and 21 CFR Part 11 compliance. Use for document control procedures, change control workflows, and electronic signature compliance.

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。

ISO 13485 internal audit expertise for medical device QMS. Use for audit planning and execution, nonconformity classification, CAPA verification, external audit preparation, or audit program 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。

CAPA system management for medical device QMS, covering root cause analysis, corrective action planning, and effectiveness verification. Use for CAPA investigations, 5-Why and fishbone analysis, and corrective action tracking.

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。

IoT network traffic analyzer for detecting IoT protocols and identifying security vulnerabilities in network communications. Use when you need to analyze network traffic, identify IoT protocols, or assess network security of IoT devices.

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。

Network flow extractor that analyzes pcap/pcapng files to identify outbound connections with automatic DNS hostname resolution. Use when you need to enumerate network destinations, identify what hosts a device communicates with, or map IP addresses to hostnames from packet 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。

Analyze digital and analog captures from Saleae Logic MSO devices. Decode protocols like UART, SPI, I2C from exported binary files. Use when analyzing logic analyzer captures for CTF challenges, hardware reverse engineering, or protocol decoding.

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。

Turn a one-line description of a repetitive task into a reusable, self-guarding slash command. loop-forge diagnoses the task into one of 5 loop shapes (Batch / Pipeline / Refine / Watch / Explore), interviews for the blanks, and auto-injects two safety devices the user didn't know they needed — an independent verifier (maker ≠ checker) and a hardstop (a budget/count/cooldown ceiling) — then previews the result and stamps it as a `/command` they can run forever. Use when the user says "/loop", "/loop-forge", "/make-it-loop", "automate this", "make this repeatable", "turn this into a command", "do this for all 100 items", "do X every time Y happens", "generate several and pick the best", or otherwise wants to capture a recurring task as a reusable slash command instead of re-typing the prompt by hand. Works in any language: it interviews the user and writes the stamped command in the user's own language. Non-goal — it does not schedule unattended runs (launchd/cron) or publish externally on its own; it stamps the reusable command and stops there.

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。

Expert debugging and profiling for leaks, GPU/Visual Profiler, headless CI QA, orphan nodes, thread-safe logs, and custom Debugger monitors — not print/breakpoint tutorials. Trigger on OBJECT_ORPHAN_NODE_COUNT, ObjectDB growth, Visual Profiler GPU spikes, flaky headless exits, or remote device consoles. Keywords: orphan nodes, Performance.get_monitor, Visual Profiler, Time.get_ticks_usec, EditorDebuggerPlugin, headless QA, push_error, backtrace.

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。

Provision, verify, and connect a self-hosted Temps platform instance on an explicitly authorized machine. Use when the user wants an agent to install Temps with the official deploy script, configure a local CLI context, start browser device authorization, present the approval URL, wait for approval, or perform initial platform, DNS, TLS, user, and service setup without exposing credentials.

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。

Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.

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 targeting Android/iOS — export and signing, permissions, plugins, in-app purchases, ads, app lifecycle, device features, and mobile 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。

Generates user-facing usage statistics, activity summaries, and personalized insights dashboards (weekly recaps, year-in-review, Spotify Wrapped-style). Use when user wants to show usage stats, activity insights, or shareable recap screens. Different from analytics-setup which sends data to a backend — this shows insights to the USER on-device.

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。

Generates an automated App Store screenshot pipeline with UI tests for screenshot capture, device framing, localized caption overlays, and multi-size batch export. Use when user wants automated screenshots, App Store screenshot generation, or a fastlane snapshot replacement.

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。

Generates an in-app feedback collection form with category selection, text input, optional screenshot attachment, device diagnostics, and smart routing — directing happy users to App Store reviews and unhappy users to support. Use when user wants feedback, bug reports, feature requests, or contact support forms.

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。

Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants. Use when implementing AI-powered 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。

On-device LLM integration using Apple's Foundation Models framework. Use when implementing AI text generation, structured output, or tool calling.

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。

Core ML, Create ML, Vision framework, Natural Language framework, on-device ML integration. Use when user wants image classification, text analysis, object detection, sound classification, model optimization, or custom model integration. Covers Core ML vs Foundation Models decision.

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。

Expert knowledge for Azure Notification Hubs development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when integrating FCM/APNS/WNS, targeting devices/users, using tags/templates, IaC config, or Private Link, and other Azure Notification Hubs related development tasks. Not for Azure Event Hubs (use azure-event-hubs), Azure Service Bus (use azure-service-bus), Azure Web PubSub (use azure-web-pubsub).

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。

Expert knowledge for Azure IoT Edge development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring EFLOW devices, DPS/X.509 provisioning, gateway/nested topologies, CI/CD deployments, or IoT Edge metrics/logs, and other Azure IoT Edge related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT (use azure-iot), Azure IoT Operations (use azure-iot-operations), Azure Stack Edge (use azure-stack-edge).

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。

Expert knowledge for Azure IoT Central development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing device templates, data exports, IoT Edge gateways, REST/CLI automation, or IoT Central migrations, and other Azure IoT Central related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT (use azure-iot), Azure IoT Edge (use azure-iot-edge), Azure IoT Operations (use azure-iot-operations).

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。

Expert knowledge for Azure Firmware Analysis development including best practices, security, integrations & coding patterns, and deployment. Use when configuring RBAC/service principals, uploading firmware via CLI/PowerShell/Python, mapping results to Device Registry, reading SBOM paths, or deploying workspaces with ARM/Bicep/Terraform, and other Azure Firmware Analysis related development tasks. Not for Azure Defender For Iot (use azure-defender-for-iot), Azure IoT Edge (use azure-iot-edge), Azure IoT Hub (use azure-iot-hub), Azure Confidential Computing (use azure-confidential-computing).

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 running in-app message campaigns, triggering/suppressing messages, configuring opt-in data collection, testing on specific devices, or handling message callbacks.

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 working on inclusion, i18n/localization, global name/address forms, low-end devices, slow/metered networks, affordability, or first-time/low-confidence users; not WCAG/screen readers (see accessibility).

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。