649 件 ・ 関連度順
概要と使いどころ
Access accelerometer, gyroscope, magnetometer, pedometer, and activity-recognition data using CoreMotion. Use when reading device sensor data, counting steps, detecting user activity (walking/running/driving), tracking altitude changes, or implementing motion-based interactions in iOS/watchOS apps.
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 research-grade sensor data using SensorKit. Use when reading ambient light levels, accelerometer data, rotation rates, device usage patterns, keyboard metrics, or media events for approved research studies. Requires SensorKit entitlement and research study authorization.
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 and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model 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。
Build alternative browser engines using BrowserEngineKit. Use when developing a non-WebKit browser engine for iOS in the EU, managing web content rendering processes, configuring GPU and networking processes for browser functionality, checking device eligibility for alternative engines, or working with BrowserEngineKit entitlements.
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。
Collect and analyze on-device performance metrics and crash diagnostics using MetricKit. Use when setting up MXMetricManager, handling MXMetricPayload or MXDiagnosticPayload, processing crash/hang/disk-write diagnostics via MXCallStackTree, adding custom signpost metrics, or uploading telemetry to an analytics backend.
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。
Transfer app data between platforms using AppMigrationKit. Use when implementing one-time data migration from Android or other platforms to iOS, managing cross-platform transfer sessions with AppMigrationExtension, packaging and archiving user data for export, importing resources on the destination device, tracking transfer progress, handling migration errors, or building onboarding flows that import existing user 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。
Discover and configure Bluetooth and Wi-Fi accessories using AccessorySetupKit. Use when presenting a privacy-preserving accessory picker, defining discovery descriptors for BLE or Wi-Fi devices, handling accessory session events, migrating from CoreBluetooth permission-based scanning, or setting up accessories without requiring broad Bluetooth permissions.
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。
Hardware Security Modules (HSMs) are tamper-resistant physical devices that safeguard cryptographic keys and perform cryptographic operations in a hardened environment. Keys stored in an HSM never lea
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。
bu skill guides organizations through implementing zero trust architecture in cloud environments following NIST SP 800-207 and Google BeyondCorp principles. It covers identity-centric access controls, micro-segmentation, continuous verification, device trust assessment, and Dağıt:ing Identity-Aware Proxy to eliminate implicit network trust in AWS, Azure, and GCP 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。
bu skill covers implementing Okta as a centralized identity provider for cloud environments, configuring SSO integration with AWS, Azure, and GCP, Dağıt:ing phishing- resistant MFA with Okta FastPass, managing lifecycle automation for user provisioning and deprovisioning, and enforcing adaptive access policies based on device posture and risk signals.
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。
Spotify: play, search, queue, manage playlists and 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。
Track Apple devices/AirTags via FindMy.app on macOS.
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 controlling NVIDIA Broadcast through MCP to apply effects, process local media, select devices, or change camera resolution, or when Broadcast is missing or too old to expose the gateway and the user wants it installed; not for Broadcast app settings outside the MCP gateway.
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。
Detect OAuth access token theft and misuse by analyzing sign-in logs for impossible travel, new device patterns, token replay from unusual IPs, and anomalous scope requests via Microsoft Graph and Okta APIs.
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。
Detects and analyzes Bluetooth Low Energy (BLE) security attacks including sniffing, replay attacks, GATT enumeration abuse, and Man-in-the-Middle interception. Uses Ubertooth One and nRF52840 sniffers for packet capture, the bleak Python library for GATT service enumeration, and crackle for BLE encryption cracking. Use when assessing IoT device BLE security, monitoring for BLE-based attacks on wireless infrastructure, or performing authorized BLE penetration testing. Activates for requests involving BLE security assessment, Ubertooth sniffing, GATT enumeration, or BLE replay detection.
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。
Deploying Cloudflare Access with Cloudflare Tunnel to provide zero trust access to self-hosted and private applications, configuring identity-aware access policies, device posture checks, and WARP client enrollment for VPN 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。
This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.
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。
Configuring Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring access policies based on user identity and device posture, and integrating with IdPs.
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。
Configure secure OAuth 2.0 authorization flows including Authorization Code with PKCE, Client Credentials, and Device Authorization Grant. This skill covers flow selection, PKCE implementation, token
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。
Hardware Security Modules (HSMs) are tamper-resistant physical devices that safeguard cryptographic keys and perform cryptographic operations in a hardened environment. Keys stored in an HSM never lea
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 Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points. This skill covers Duo integration methods, adaptive authentication policies, device trust
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。
Parse and analyze Windows Amcache.hve registry hive to extract program execution evidence, file metadata, SHA-1 hashes, and device connection history for digital forensics and incident response investigations.
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。
Inspects PostHog Web analytics Live tab data — current users online, last-30-minutes pageviews, top pages, referrers, devices, browsers, countries, bot traffic, and the per-minute bot/users charts. Use when the user asks "who is on my site right now?", "what is happening live?", "what bots are crawling me?", asks about the "live tab" / "live dashboard", wants live numbers (last 30 min), or wants help filtering or drilling into the live view. Also covers building product-analytics insights that mirror what the tiles show.
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。
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
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。