Skill UI

Aeon is a scikit-learn compatible toolkit for time series machine learning, covering classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, and feature extraction on temporal data.

Access over 800,000 economic time series from FRED's API, covering GDP, employment, inflation, interest rates, regional metrics, and more; ideal for macroeconomic analysis, financial research, policymaking, and forecasting workflows.

Connect to NCBI's GEO repository, search series/samples/platforms via Entrez queries, fetch profiles, and download raw/processed matrices using GEOparse for transcriptomics and expression analysis workflows.

Access aggregated OFR hedge fund time series and metadata without auth, covering Form PF stats, repo volumes, futures trader positioning, and leverage/counterparty metrics for risk monitoring or research.

Query and download the NCI Imaging Data Commons public cancer imaging datasets via idc-index, filter by metadata, fetch DICOM files, visualize series, and respect licensing details for AI training or research.

Statsmodels is a comprehensive Python library dedicated to advanced statistical modeling and econometrics. It provides tools for rigorous statistical inference, including Ordinary Least Squares (OLS), Generalized Linear Models (GLM), mixed-effects models, and time series analysis (ARIMA). Use this skill for detailed diagnostics, coefficient estimation, hypothesis testing, and producing publication-ready statistical reports in fields like econometrics and biostatistics.

This skill provides zero-shot time series forecasting using Google's TimesFM foundation model. It forecasts any univariate time series (like sales, sensor data, or weather) without requiring custom model training. The model delivers point forecasts along with calibrated prediction intervals (quantiles), offering a robust and probabilistic view of future trends. It is ideal for rapid, reliable forecasting across diverse time-based datasets.

This tool detects abnormal access patterns across major cloud storage services (AWS S3, GCS, Azure Blob Storage). By analyzing audit logs like CloudTrail, it uses statistical baselines and time-series anomaly detection to identify suspicious activities such as after-hours bulk downloads, access from new IPs, or unusual API call spikes. It is crucial for investigating potential data exfiltration incidents or building robust cloud security detection rules.

This skill provides programmatic access to comprehensive global financial market data via the Alpha Vantage API. Users can retrieve time-series data, including historical prices (OHLCV) for equities, options, forex, commodities, and crypto. It also provides access to fundamental metrics (e.g., P/E ratio, market capitalization), economic indicators (e.g., GDP, CPI), and over 40 technical indicators (e.g., RSI, MACD), making it ideal for quantitative analysis and financial modeling.

A technique for dramatically increasing the hit rate when searching for TV series. Instead of using generic terms like genre or era, combine 2-3 highly distinctive plot details (e.g., character sacrifices, specific season incidents) into a single query. This method leverages the unique nature of plot points to pinpoint specific shows quickly.

Scikit-learn compatible Python toolkit for time series machine learning: classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search and distance metrics for univariate and multivariate temporal data.

Guidance and local audit tools for Python workflows using GeoPandas GeoSeries, GeoDataFrame, spatial operations, CRS handling, and vector-data I/O. Includes safety gates for provenance, geometry validity, and privacy-aware geodata sharing.