Azure Maps SDK for .NET. Location-based services including geocoding, routing, rendering, geolocation, and weather. Use for address search, directions, map tiles, IP geolocation, and weather 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。
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概要と使いどころ
Azure Maps SDK for .NET. Location-based services including geocoding, routing, rendering, geolocation, and weather. Use for address search, directions, map tiles, IP geolocation, and weather 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。
Automate Ambient Weather tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Azure Maps SDK for .NET. Location-based services including geocoding, routing, rendering, geolocation, and weather. Use for address search, directions, map tiles, IP geolocation, and weather 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。
Azure Maps SDK for .NET. Location-based services including geocoding, routing, rendering, geolocation, and weather. Use for address search, directions, map tiles, IP geolocation, and weather 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。
Get current weather and forecasts (no API key required).
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 p5.js/canvas for local procedural character effects: particles, weather, squash/stretch, walk cycles, and environmental motion.
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。
Asset allocation theory and optimizer usage — MPT / Black-Litterman / risk budgeting / all-weather strategy, including guides for 5 optimizers and rebalancing rules.
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。
Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Supports both basic forecasting and advanced covariate forecasting (XReg) with dynamic and static exogenous variables. Automatically checks system RAM/GPU before loading the model, validates dataset fit before processing, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model and handle your specific dataset.
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 conditions include storms, flooding, heat waves, or other hazards.
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。
Replays a CARLA .log recorded by the recorder — the whole run or a time window, at any speed, following a chosen actor, optionally regenerating sensors and restoring weather. Use when the user asks to "replay the recording", "play back the run", "watch it again in slow motion / at 2x", "follow vehicle N during replay", or "replay onto a different map".
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。
Controls the map's light sources through the CARLA LightManager — turn street lamps, building/facade lights, vehicle lights or all of them on/off, set their colour and intensity, and toggle the automatic lights-at-night cycle. Use when the user asks to "turn on the street lights", "light up the city at night", "turn off building lights", "change the street-light colour", or "make lights come on automatically at night". Distinct from hiding lamp meshes (toggle-env-objects) and the sun (set-weather).
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。
Call MCP Server tools directly via the mcporter CLI. Use when you need to interact with external APIs (GitHub, weather, etc.) without delegating to a Worker — useful for quick lookups or when you need a result to make a 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。
Use when admin asks to configure an MCP tool server (e.g., GitHub, weather API), rotate credentials, grant/revoke worker access to MCP tools, or add a custom API integration via YAML.
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。
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
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。
Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Automatically checks system RAM/GPU before loading the model, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model. For classical statistical time series models (ARIMA, SARIMAX, VAR) use statsmodels; for time series classification/clustering use aeon.
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。
Pay-per-call access to the Hexanon family of eight x402 APIs for autonomous agents — no signup, no API keys, USDC on Base. Covers US/Canada vehicle & VIN intelligence (Vindex), e-commerce demand signals (Demandex), Polymarket whale intelligence (OrcaTrace), GitHub trending-repo digests (gitBeacon), narrative intelligence (Signalis), Moltbook community digests (Moltalyzer), x402 seller conformance scanning (x402lint), and Polymarket weather-market signals (Isocast).
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。
Find Earth2Studio models, data sources, and examples for a weather/climate use case. Do NOT use for writing inference code, downloading data, or installation.
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。
Baidu Maps skill for location search, nearby place search, geocoding, route planning, and weather queries. Use when user needs map services, location information, or navigation within China.
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。
Download flood stage thresholds from NWS (National Weather Service). Use when determining flood levels for USGS stations, accessing action/minor/moderate/major flood stages, or matching stations to their flood thresholds.
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 work crosses into Apple's system surfaces rather than your own UI or data — Siri and Shortcuts, widgets, Live Activities, in-app purchase, localization, privacy prompts, alarms, timers, calendar, reminders, contacts, SharePlay, VoIP and CallKit, accessory pairing, weather, Spotlight indexing, background tasks, Background Assets, push, or push on networks with no internet.
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。
Compute aerospace environment properties including atmosphere (ISA, COESA, NRLMSISE-00, non-standard, CIRA), gravity (spherical harmonic, WGS84, zonal, centrifugal), horizontal wind (HWM), magnetic field (WMM, IGRF), geoid height, geocentric radius, space weather data, planetary ephemeris, Earth orientation (polar motion, nutation, delta-UT1, CIP). Use when computing atmospheric density, temperature, pressure, gravity vectors, wind profiles, magnetic field components, geoid undulation, solar flux indices, planet positions, or Earth orientation parameters for aerospace vehicle analysis, spacecraft environment modeling, or navigation corrections.
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 blueprint for GPU particle systems (explosions, magic effects, weather, trails) using GPUParticles2D/3D, ParticleProcessMaterial, gradients, sub-emitters, and custom shaders. Use when creating VFX, environmental effects, or visual feedback. Keywords GPUParticles2D, ParticleProcessMaterial, emission_shape, color_ramp, sub_emitter, one_shot.
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 Maps development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Azure Maps Web/REST SDKs, geocoding, routing, traffic, weather tiles, or Power BI visual integrations, and other Azure Maps related development tasks.
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。
将天气要素(风速、能见度、降雨量等)单站预报系统的项目文档、模型、报告、评估结果整理成符合省级自然科学基金项目编写规范的专题研究报告。适用于:(1) 基于Claude Code + OpenSpec开发的气象预报系统结题报告编写,(2) 将技术文档转换为学术研究报告格式,(3) 生成符合省级自然科学基金规范的专题研究报告,(4) 整合项目代码、模型、评估指标等技术材料为规范化学术报告。触发关键词:"专题研究报告"、"结题报告"、"天气预报系统"、"基金项目报告"、"风速预报"、"能见度预报"、"降雨量预报"、"气象预测"、"单站预报"等。
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。