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Found 18 Skills
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Process Excel files with data manipulation, formula generation, and chart creation. Use when working with spreadsheets or Excel data.
Automate Google Sheets operations (read, write, format, filter, manage spreadsheets) via Rube MCP (Composio). Read/write data, manage tabs, apply formatting, and search rows programmatically.
Best practices for Pandas data manipulation, analysis, and DataFrame operations in Python
Manage Google Sheets spreadsheets. Read/write cell values and ranges, manage sheets, formatting, and formulas. Use when working with Google Sheets spreadsheet management.
This skill should be used when the user asks to "read spreadsheet", "write to sheet", "create spreadsheet", "list spreadsheets", "google sheets", "read cells", "write cells", "append rows", "sheet data", or mentions Google Sheets operations. Provides Google Sheets API integration for reading, writing, and managing spreadsheets.
Read and write Google Sheets data. Load when user mentions 'google sheets', 'spreadsheet', 'update sheet', 'read sheet', 'append to sheet', or references extracting data to update a tracking sheet.
Python data analysis with pandas, numpy, and analytics libraries
This skill should be used when the user asks to "use pandas", "analyze data with pandas", "work with DataFrames", "clean data with pandas", or needs guidance on pandas best practices, data manipulation, performance optimization, or common pandas patterns.
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
Master SQL fundamentals including SELECT, INSERT, UPDATE, DELETE, CREATE, ALTER, DROP operations. Learn data types, WHERE clauses, ORDER BY, GROUP BY, and basic joins.
Command-line JSON processor. Extract, filter, transform JSON.