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Found 278 Skills
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.
Parse, analyze, and process SARIF (Static Analysis Results Interchange Format) files. Use when reading security scan results, aggregating findings from multiple tools, deduplicating alerts, extracting specific vulnerabilities, or integrating SARIF data into CI/CD pipelines.
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.
Find stocks with consensus sentiment across multiple finance YouTubers. Use when looking for stocks that multiple bloggers agree on (bullish or bearish).
Analyze tonality — key detection, chord progression, melody contour
Construct a business cycle model using leading and coincident indicators, and interpret two business cycle phases: Expansion (Risk-On) and Contraction (Risk-Off), and generate "Iceberg" and "Sinking" event signals based on the theory.
Analyze the BTC market using a custom momentum theory with nested multi-timeframe analysis (2-day/1-day/12h/6h/4h/2h/1h/30min). Identify uptrend segments, downtrend segments, discrete regulation, unit adjustment cycles, continuous gap divergences, and DIF-DEA divergences, and generate momentum reports with detailed attribute judgments and trading signals. Automatically activates when users inquire about BTC momentum, segment status, MACD analysis, cycle judgment, or divergence detection.
Pyspark Transformer - Auto-activating skill for Data Pipelines. Triggers on: pyspark transformer, pyspark transformer Part of the Data Pipelines skill category.
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
Guide Claude through ingesting TCGA sample sheets, expression archives, and clinical carts into omicverse, initialising survival metadata, and exporting annotated AnnData files.
Index points into a hexagonal grid
Analyze metabolomics data including metabolite identification, quantification, pathway analysis, and metabolic flux. Processes LC-MS, GC-MS, NMR data from targeted and untargeted experiments. Performs normalization, statistical analysis, pathway enrichment, metabolite-enzyme integration, and biomarker discovery. Use when analyzing metabolomics datasets, identifying differential metabolites, studying metabolic pathways, integrating with transcriptomics/proteomics, discovering metabolic biomarkers, performing flux balance analysis, or characterizing metabolic phenotypes in disease, drug response, or physiological conditions.