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Found 213 Skills
Research prediction markets - base rates, resolution rules, historical data
Compare two CSV files and generate a unified diff file showing line-by-line differences.
Researches SEC filings, earnings calls, analyst reports, and market data. Use when the album subject involves financial crimes, corporate stories, or market events.
Use the whoo CLI to retrieve and interpret WHOOP health data: recovery score, HRV, sleep quality, strain, SpO2, and body measurements. Invoke when the user asks about their WHOOP metrics, readiness, fitness recovery, sleep performance, wearable health data, or wants to pull or analyze WHOOP data for any date range.
Use this for exploratory data analysis (EDA), generating visualizations, finding trends, and deriving insights from datasets using Python (Pandas/Seaborn/Plotly) or SQL.
Microsoft Excel (.xlsx) spreadsheet manipulation using MCP server tools. Use this any time an Excel spreadsheet is involved - as input, output, or both. Activate the excel-server MCP for Excel operations. Covers creating workbooks, managing worksheets, formatting cells, writing formulas, creating charts, building pivot tables, and data analysis with professional standards.
Best practices for doing quick exploratory data analysis with minimal code and a Pandas .plot like API using HoloViews hvPlot.
Analyze trends and patterns in health data over a period of time. Correlate changes in medications, symptoms, vital signs, lab results, and other health indicators. Identify concerning trends, improvements, and provide data-driven insights. Use this when users ask about health trends, patterns, changes over time, or "What's changed with my health status?" Supports multi-dimensional analysis (weight/BMI, symptoms, medication adherence, lab results, mood and sleep), correlation analysis, change detection, and interactive HTML visualization reports (ECharts charts).
Use when writing or running Nushell commands, scripts, or pipelines - via the Nushell MCP server (mcp__nushell__evaluate), via Bash (nu -c), or in .nu script files. Also use when working with structured data (JSON, YAML, TOML, CSV, Parquet, SQLite), doing ad-hoc data analysis or exploration, or when the user's shell is Nushell.