「time」の検索結果

⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.

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Detects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling. Checks if features/statistics would be available at prediction time.

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Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

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Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.

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Use this skill when administering, operating, or debugging a GoClaw gateway through the GoClaw CLI/runtime package. It covers CLI discovery, safe command inspection, gateway health/config diagnostics, agents, skills, MCP/tools, runtime packages, credentials, traces, sessions, channels, providers, cron/jobs, and troubleshooting. Always inspect the live `goclaw --help` output first because command availability is version-dependent.

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Use as the top-level router for Omniverse Realtime Viewer USD app requests and focused viewer reference documents.

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Use this skill when NeMo Relay is installed or imported but application-side runtime behavior is missing or incorrect, including load failures, inactive scopes, missing events, and plugin or adaptive wiring problems.

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Representative, point-in-time MoE training playbooks by hardware and model family. Use them as candidate seeds, then revalidate the exact runtime, semantics, topology, and steady-state throughput.

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Use this skill when the user is doing DOCA version handling — detecting the installed release, validating the four-way match across pkg-config doca-common, applications/VERSION, doca_caps --version, and bfver/mlnx-release on BlueField, reasoning about NGC container tags, looking up whether a capability is on the installed release, or diagnosing build-vs-runtime drift. Trigger even when the user does not explicitly say "DOCA version" or "four-way match" — typical implicit phrasings include "program built but does nothing on the wire", "undefined reference to a symbol the docs claim exists", "DOCA_ERROR_NOT_SUPPORTED at runtime", "counter didn't increment", "what does `latest` mean for this tag", or "is my LTS still supported". Refuse and route elsewhere for installing or choosing DOCA packages (doca-setup), per-library API/capability questions (matching library skill), the cross-library DOCA_ERROR_* taxonomy (doca-programming-guide), or the general debug ladder (doca-debug) — those belong to other skills.

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Use this skill when the user is debugging any DOCA symptom — a build that won't compile, a link step that can't resolve a doca_* symbol, a runtime call returning DOCA_ERROR_*, a silent service or tool, or a stack trace / valgrind / core dump — and needs the layered ladder (install → version → build → link → runtime → program → driver), verbosity controls (--sdk-log-level, DOCA_LOG_LEVEL, the doca-{lib}-trace flavor), container-debug constraints, or how to capture state for a Developer Forum post. Trigger even when the user does not say "DOCA debug" — implicit phrasings include "undefined reference to doca_*", "how do I get more logs", "packets aren't reaching the wire", "doca_caps returned nothing", or "hugepages empty in the container". Refuse and route elsewhere for library-specific debug (Flow pipe trace, RDMA QP, Comch stats), env-class pkg-config or hugepages symptoms, the DOCA_ERROR_* taxonomy and lifecycle interpretation, and performance or incident-response work — those belong to other skills.

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Query TradingView market data through the bundled tradingview MCP server without a desktop app or login. Use whenever the user wants a technical analysis readout (RSI, MACD, Bollinger rating, BUY/SELL summary), multi-timeframe alignment (weekly→daily→4h→1h→15m), exchange-wide scans (Bollinger squeeze, volume breakout, consecutive candles, smart volume), top gainers/losers by exchange, futures market data (NQ/ES/CL/GC overview, overnight movers, category snapshots), pre-market / after-hours quotes, a quick options chain or unusual options activity (volume/OI by strike), bulk stock prices, a global market snapshot, strategy backtests (Sharpe, drawdown, win rate), or crypto exchange scans. Triggers include "TA on X", "multi-timeframe read", "BB squeeze scan", "futures movers", "NQ overnight", "pre-market price", "unusual options activity", "backtest RSI on AAPL", and "top gainers on NASDAQ". For options greeks, watchlists, alerts, or chart screenshots use tradingview-reader instead.

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[omh] Vague, underspecified request: one-question-at-a-time clarification. Use when the user says: deep-interview, interview me, clarify, feature shaping, ambiguous product request, one question, 要件を詰めて, 曖昧な要求.

[omh] Live view of running coding units: showing which coding units are running right now, on which runtime and model, with observed tokens and elapsed time. Use when the user says: running-work-board, running work board, which units are running, what models are running, 지금 뭐 돌고 있어, 뭐가 돌고 있어, 어떤 모델로 돌고 있어, 실행 중인 작업 보여줘.

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[omh] Software slowness, memory leaks, or cost spikes: find where a system is actually slow, leaking, or expensive across runtime, memory, token cost, storage, rendering, inference, CI, and query domains, then fix one measured hot path at a time behind a regression budget. Use when the user says: ultraperf, ulw-perf, performance audit, performance bottleneck, find the bottleneck, profile the hot path, memory leak investigation, token cost hotspot.

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[omh] Rust ownership, lifetime, or unsafe trouble: prepare Rust changes with ownership, error, and API discipline, and escalate any unsafe, FFI, or lock-free change to the UB checklist. Use when the user says: rust, rust code, rust skill, rustlang, borrow checker, lifetime error, ownership error, trait bound.

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Control the live Pebrel terminal workspace from Codex or Claude Code. Use whenever the user asks to split panes, open a tab or file, run a command in another pane, start or prompt Codex/Claude, delegate a task to another agent, read output, wait for an agent, or says 分屏、开一个 Codex/Claude、打开 README、在上面/下面/左边/右边操作、把这个任务派给 Codex/Claude、让 codex 去改、问问另一个 agent、看看它跑完了没. Run `pebrel env` to orient, then use the supported Runtime API immediately instead of scanning processes or source code.

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。

Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection.

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Troubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. WHEN: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, message lock expired, lock renewal, lock renewal batch, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter, batch processing lock, session lock expired, idle timeout, connection inactive, link detach, slow reconnect, session error, duplicate events, offset reset, receive batch.

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Azure Queue Storage JavaScript/TypeScript SDK (@azure/storage-queue) for message queue operations. Use for sending, receiving, peeking, and deleting messages in queues. Supports visibility timeout, message encoding, and batch operations. Triggers: "queue storage", "@azure/storage-queue", "QueueServiceClient", "QueueClient", "send message", "receive message", "dequeue", "visibility timeout".

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Build real-time messaging applications using Azure Web PubSub SDKs for JavaScript (@azure/web-pubsub, @azure/web-pubsub-client). Use when implementing WebSocket-based real-time features, pub/sub messaging, group chat, or live notifications.

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Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket. Triggers: "VoiceLiveClient java", "voice assistant java", "real-time voice java", "audio streaming java", "voice activity detection java".

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 Web PubSub Service SDK for Python. Use for real-time messaging, WebSocket connections, and pub/sub patterns. Triggers: "azure-messaging-webpubsubservice", "WebPubSubServiceClient", "real-time", "WebSocket", "pub/sub".

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 real-time chat applications with Azure Communication Services Chat Java SDK. Use when implementing chat threads, messaging, participants, read receipts, typing notifications, or real-time chat features.

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Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient".

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。