Loading...
Loading...
Found 20 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.
Pandas data manipulation with DataFrames. Use for data analysis.
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.
Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Parse, transform, and analyze CSV files with advanced data manipulation capabilities.
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.
Essential patterns, idioms, and gotchas for writing Nushell code. Use when writing Nushell scripts, functions, or working with Nushell's type system, pipelines, and data structures. Complements plugin development knowledge with practical usage patterns.
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.
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.