Results for “time”

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Video and audio perception, indexing, and editing. Ingest files/URLs/live streams, build visual/spoken indexes, search with timestamps, edit timelines, add overlays/subtitles, generate media, and crea

Write, review, debug, or test Python asyncio code involving coroutines, Tasks, TaskGroups, cancellation, timeouts, queues, synchronization, and blocking-call boundaries.

Econometrics skill for time series analysis. Activates when the user asks about: "time series", "stationarity", "unit root test", "ADF test", "KPSS test", "ARIMA", "ARMA", "autocorrelation", "ACF", "PACF", "VAR model", "VECM", "Granger causality", "cointegration", "impulse response function", "forecast", "seasonal decomposition", "ARCH", "GARCH", "时间序列", "平稳性检验", "单位根", "自回归", "格兰杰因果", "协整", "脉冲响应", "预测", "向量自回归"

Econometrics skill for time series analysis. Activates when the user asks about: "time series", "stationarity", "unit root test", "ADF test", "KPSS test", "ARIMA", "ARMA", "autocorrelation", "ACF", "PACF", "VAR model", "VECM", "Granger causality", "cointegration", "impulse response function", "forecast", "seasonal decomposition", "ARCH", "GARCH", "时间序列", "平稳性检验", "单位根", "自回归", "格兰杰因果", "协整", "脉冲响应", "预测", "向量自回归"

Build real-time voice AI applications with bidirectional WebSocket communication using the Azure AI Voice Live SDK for .NET.

Polls a local relay for animation-refinement jobs from the Timeline Inspector, posts suggestions or applies changes to transition code.

Provides scikit-learn compatible algorithms for time series machine learning, including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search.

Perform astronomical research and data analysis with coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Traces design decisions and concepts through session history, handoffs, git, and artifacts, producing a chronological timeline report with citations.

Performs time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using the aeon toolkit.

Defines a time-bounded, focused work session to produce a specific creative or productive output, tracking progress and completion.

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

Capacity Planning — Real-Time Agent Workload Tracking

The layers trade timeliness against definitiveness.

Send real-time messages and manage WebSocket connections using Azure Web PubSub Service SDK for Python.

Audit and improve GitHub Codespaces efficiency by analyzing devcontainer configurations, machine sizing, prebuild strategy, and idle timeout settings.

Automate Ably real-time messaging operations through Composio's toolkit via Rube MCP, with tool discovery and connection management.

Automate time tracking, project management, and invoicing in Harvest by logging hours, managing projects, clients, and tasks through natural language commands.

Manage HR operations in Workday, including workers, time off requests, absence balances, and employee data through natural language commands.

Create professional, dark-themed SVG diagrams of any type — architecture, flowcharts, sequence, structural, mind maps, timelines, and more.

Exports a timeline.json as a Premiere Pro editor packet, including FCP7 XML, captions, and media, with verification steps.

Write, review, debug, test, or optimize pandas Series, DataFrame, Index, groupby, merge, reshape, dtype, missing-value, and time-series code.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Build real-time chat applications with thread management, messaging, participants, and read receipts using the Azure Communication Services Chat Java SDK.

Retrieves live messages from iMessage, DMs, or other messaging surfaces to read texts, recover one-time codes, or inspect threads before replying.

Apply the Doherty Threshold to keep system response times under 400ms, maintaining user flow and perceived performance.

Creates a hero frame with looping CSS animations including a rotating type ring, animated globe, ticking timer, and parallax labels.

Runs time series machine learning tasks—classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search—using the scikit-learn compatible aeon toolkit.

Guides feature extraction and preprocessing for time series data using aeon transformers, covering collection and series transformers with code examples.

Project estimation and time management for agent-orchestrated builds.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Zero-shot univariate time-series forecasting with Google's TimesFM foundation model, producing point forecasts and prediction intervals from CSV/DataFrame/array inputs, with a preflight system checker for RAM/GPU. Use to forecast any univariate series (sales, sensors, energy, vitals, weather) without training a custom model. Part of the AlterLab Academic Skills suite.