「snow」の検索結果

Think and work like an expert Hydrologist. Use when a task calls for Hydrologist judgment. Reasons from hydrologic-cycle closure (P = ET + Q + ΔS + I), runoff-generation mechanisms, and channel routing through HEC-HMS, HEC-RAS, the National Water Model, and split-sample KGE/NSE/PBIAS calibration, while treating post-flood rating-curve shifts, radar QPE bias, snow/rain misclassification, and non-stationarity in extremes as first-class failure modes.

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。

Architecture-first UI/UX design skill for Codex that helps agents reason from product truth, user journeys, causal design decisions, art direction, interaction, responsive behavior, imagery, iconography, and motion before implementation, then validate the result through rendered browser critique.

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。

dlt (data load tool) is an open-source Python library that loads data from APIs, files and databases into warehouses and lakes, inferring the schema and tracking incremental state for you. Use when a user asks to build a data pipeline in Python, load a REST API into DuckDB, BigQuery, Snowflake or Postgres, set up incremental or merge loading, enforce a schema contract, or replace a hand-written ETL script or a hosted ELT connector.

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。

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

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。

Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.

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 FinOps guidance for cloud, AI, and SaaS technology spend. Covers AI cost management, agentic FinOps, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, open-weight vendor APIs (DeepSeek, Qwen, Kimi, GLM), AWS (EC2, Bedrock, SageMaker, Savings Plans, CUR), Azure (reservations, AHB, OpenAI PTUs), GCP (Vertex AI, BigQuery), OCI, Kubernetes cost allocation, data platforms (Databricks, Fabric F-SKUs, Snowflake), tagging governance, SaaS management (SAM, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Codex), ITAM, allocation, showback, chargeback, anomaly management, KPIs and benchmarking, waste detection playbooks, workload onboarding and M&A, and GreenOps (cloud carbon, CSRD). Use for any question about technology cost or waste in your estate - expiring commitments or RIs, NAT gateway bills, idle VMs, snapshot sprawl - and for commitment sizing, rightsizing, allocation, SaaS sprawl, AI dev tool spend, or connecting spend to business value. Built by OptimNow.

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。

文章风格深度分析（通用版，不限平台）。当用户想研究某个作者/账号/媒体的写作风格、拆解爆款套路、对比不同账号风格差异、或想"一键生成模仿某风格的写作 skill"时使用。触发场景包括："帮我分析这个公众号的风格"、"研究下这些文章的写法"、"拆解这个大V的套路"、"对比这两个号"、"我想学习XX的写作风格"、"基于这些样本做个仿写技能"。即使用户只是说"帮我看看这些文章"或"研究下这个号"，如果提供了多篇文章样本，也应触发。适用于公众号、知乎、小红书、Twitter/X、博客、学术期刊、个人散文、新闻媒体等任意中长文样本。

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。

Evaluate current trail conditions including weather, snow line, river crossings, exposure, and trail maintenance status for safety decision-making. Produces a GREEN/YELLOW/RED safety rating with actionable go/no-go recommendations. Use the day before or morning of a planned hike, during tour planning to assess seasonal viability, after unexpected weather changes on a multi-day tour, when reports suggest trail damage or closures, or before committing to an alpine or exposed route.

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。

在创意写作、头脑风暴、方案设计、内容创作、分析与观点表达等任务中，当输出的价值不只由准确性决定、而是由视角和表达决定时，调用此 skill。它帮助 AI 识别自己的默认生成路径，并在输出前刻意偏离，产出有性格、有立场、令人难忘的内容。

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 a task needs the judgment of an airfield operations specialist — running a Part 139 self-inspection of the movement area, assigning a Runway Condition Code (RwyCC) after snow/ice contamination, deciding whether a discovered hazard needs an immediate NOTAM, triggering a Wildlife Hazard Assessment after a strike or sighting, or judging a FOD find as immediate-closure versus scheduled removal.

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 this skill when configuring Data Manager in CRM Analytics: enabling objects for sync, scheduling data sync runs, setting up remote connections to external databases, monitoring sync status and error logs, or troubleshooting connected object issues. Trigger keywords: data sync, connected objects, Data Manager, sync schedule, remote connection, Snowflake connector, sync error, incremental sync, CRM Analytics data pipeline. NOT for pushing external data in programmatically via the External Data API — use data/analytics-external-data. NOT for authoring dataflow nodes — use admin/analytics-dataflow-development.

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 debt payoff software — avalanche vs snowball strategy engines, interest calculation accuracy, amortization schedules, payment scheduling automation, credit score impact modeling, hardship accommodation workflows, and progress visualization.

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。

วางแผนการเงินส่วนตัว — งบประมาณ 50/30/20, emergency fund, ลดหนี้ snowball/avalanche, ลงทุน, เกษียณ FIRE Thailand

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。

Firmware development for the ESP32-C3 0.42" OLED board (ESP32-C3FH4, QFN32) — the ABRobot / 01Space "ESP32-C3-0.42LCD" mini board and its clones, sold as "ESP32-C3 SuperMini with OLED" and "ESP32 C3 OLED development board". Covers its 72x40 SSD1306 OLED on I2C, the single I2C bus, blue LED on GPIO8, BOOT button on GPIO9, USB Serial/JTAG console, ADC1, Wi-Fi/BLE, and the ESP-IDF + PlatformIO setup around them. Use when working on this board or a bare ESP32-C3: project setup, platformio.ini and sdkconfig, pin mapping and strapping pins, getting the 0.42-inch display to show something other than snow, U8g2 offsets, adding a second I2C device, flashing over USB-C, or debugging why something on the board does not work.

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。

Technical blog post writing guide. rooftopsnow.tistory.com style — Korean formal technical prose, architecture diagrams, code blocks + design intent commentary, table comparisons, checklist wrap-up. Triggers on "blog", "포스팅", "블로그", "기술 글", "tech blog".

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。

Validate and implement Sinclair ZX Spectrum 16K/48K ULA and board-level behavior in the EMULATORS repository, including PAL/NTSC raster timing, bitmap and attribute fetches, FLASH/BRIGHT/INK/PAPER rendering, CPU clock generation, lower-RAM and I/O contention, floating bus, snow effect, DRAM addressing and refresh, port FE keyboard/tape/border/sound behavior, interrupts, and ULA revision boundaries. Use when Codex reviews or edits namespace ZXSPECTRUM ULA, ULARegisters, Memory, PortManager, Screen, Sound, Datasette, Z80 bus timing, raster, contention, or ZX Spectrum hardware tests.

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。

Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture

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。

Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on. Use when the user wants to "connect Stripe", "import data from Postgres", "add a new data source", "sync my warehouse tables", or wants to pick sync methods for each table. Walks through source-type discovery, credential validation, table discovery, per-table sync_type selection, and the final create call. Also covers picking a good prefix and what to do right after creation.

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 the user asks about revenue, payments, subscriptions, billing, CRM deals, support tickets, production database tables, or other data that PostHog does not collect natively. Also use when a query fails because a table does not exist or returns no results for expected external data. The data warehouse can import from SaaS tools (Stripe, Hubspot, etc.), production databases (Postgres, MySQL, BigQuery, Snowflake), and other arbitrary data sources. Covers checking existing sources, identifying the right source type, and guiding the setup.

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。

Import a single webpage from any URL into canonical EDS block format — structured HTML that authors edit in DA. Scrapes the page, analyzes structure, maps to existing blocks, and generates HTML for immediate local preview. Also triggered by terms like "migrate", "migration", or "migrating". Use this when the goal is canonical EDS authoring; use the snowflake skill instead when the user wants to preserve the original DOM byte-for-byte (static-to-EDS overlay).

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。

Static-to-EDS conversion that preserves the original design while making content authorable in Document Authoring. Two modes — page-level (overlay template with slot markers) and block-level (each section becomes an independent EDS block). Use when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived hand-coded, etc.) into an Edge Delivery Services page. Triggers on "convert this page to EDS", "static-to-EDS overlay", "convert to EDS blocks", "next experimentation", "next run", "start run", or when a user provides a source URL and asks to make it editable in DA while keeping the original design intact. Do NOT use for canonical EDS block-rewrite migrations — that's the page-import 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。

Use when a carrier or driver asks about winter trucking, snow chain requirements, hot-weather precautions, summer tire failures, fuel additive use (anti-gel), idle management in extreme temperatures, weight restrictions in spring thaw, or how seasonal demand patterns affect freight rates and capacity.

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。

Import a single webpage from any URL into canonical EDS block format — structured HTML that authors edit in DA. Scrapes the page, analyzes structure, maps to existing blocks, and generates HTML for immediate local preview. Also triggered by terms like "migrate", "migration", or "migrating". Use this when the goal is canonical EDS authoring; use the snowflake skill instead when the user wants to preserve the original DOM byte-for-byte (static-to-EDS overlay).

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。

Static-to-EDS conversion that preserves the original design while making content authorable in Document Authoring. Two modes — page-level (overlay template with slot markers) and block-level (each section becomes an independent EDS block). Use when converting an AI-generated static HTML page (Stardust, Mobirise, Relume, Lovable, v0, Figma-derived hand-coded, etc.) into an Edge Delivery Services page. Triggers on "convert this page to EDS", "static-to-EDS overlay", "convert to EDS blocks", "next experimentation", "next run", "start run", or when a user provides a source URL and asks to make it editable in DA while keeping the original design intact. Do NOT use for canonical EDS block-rewrite migrations — that's the page-import 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。