Total 30,741 skills, Data Processing has 1471 skills
Showing 12 of 1471 skills
Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.
Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.
Data modeling with Entity-Relationship Diagrams (ERDs), data dictionaries, and conceptual/logical/physical models. Documents data structures, relationships, and attributes.
SerpApi search engine results API via curl. Use this skill to scrape Google, Bing, YouTube, and other search engines.
Clean and transform messy data in Stata with reproducible workflows
Run IV, DiD, and RDD analyses in R with proper diagnostics
Track and analyze whale wallets on Solana - identify smart money, cluster related wallets, detect accumulation/distribution patterns, and filter signal from noise. Use for alpha generation and risk assessment.
Panel data analysis with Python using linearmodels and pandas.
This skill should be used when analyzing business sales and revenue data from CSV files to identify weak areas, generate statistical insights, and provide strategic improvement recommendations. Use when the user requests a business performance report, asks to analyze sales data, wants to identify areas of weakness, or needs recommendations on business improvement strategies.
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table/view management, external tables, schema operations, query templates, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP/LSP server integration for AI-assisted querying and editor support. Modern Rust-based replacement for the Python `bq` CLI with faster startup, better cost awareness, and streaming support. Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files), with support for Cloud Storage integration.
Instructions for fetching current weather temperature data for Karachi, Pakistan from wttr.in API
Find stocks with consensus sentiment across multiple finance YouTubers. Use when looking for stocks that multiple bloggers agree on (bullish or bearish).