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Found 30 Skills
Create and manipulate Microsoft Excel workbooks programmatically. Build spreadsheets with formulas, charts, conditional formatting, and pivot tables. Handle large datasets efficiently with streaming mode.
Automatically generate Excel reports from data sources including CSV, databases, or Python data structures. Supports data analysis reports, business reports, data export, and template-based report generation using pandas and openpyxl. Activate when users mention Excel, spreadsheet, report generation, data export, or business reporting.
Create, edit, and manipulate Excel spreadsheets programmatically using openpyxl
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified. Originally from OpenAI's curated skills catalog.
Handle spreadsheet operations (Excel/CSV) with high-fidelity modeling, financial analysis, and visual verification. Use for budget models, data dashboards, and complex formula-heavy sheets. Use proactively when zero formula errors and professional standards are required. Examples: - user: "Build an LBO model" -> create Excel with banking-standard formatting - user: "Analyze this data and create a dashboard" -> use openpyxl + artifact_tool - user: "Verify formulas in this spreadsheet" -> run recalc.py to check for errors
Reads Excel (.xlsx) files and converts to Markdown format. Handles multiple sheets and large tables. Use when needing to read Excel spreadsheets. Requires openpyxl package.
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
Comprehensive Excel spreadsheet creation, editing, and analysis using openpyxl and xlwings supporting formulas, formatting, data analysis, charts, and financial model color coding. Use when asked to "create a spreadsheet", "edit this Excel file", "analyze spreadsheet data", "preserve Excel formulas", "create financial model", or "recalculate formulas". Implements industry-standard color conventions (blue=inputs, black=formulas, green=internal links, red=external links, yellow=key assumptions) and zero formula error requirements. Works with .xlsx, .xlsm, .csv, .tsv files for professional spreadsheet workflows.
Create, parse, and control Excel files on macOS. Professional formatting with openpyxl, complex xlsm parsing with stdlib zipfile+xml for investment bank financial models, and Excel window control via AppleScript. Use when creating formatted Excel reports, parsing financial models that openpyxl cannot handle, or automating Excel on macOS.
Python data processing with pandas, openpyxl, and lxml. Covers DataFrame operations, Excel I/O, XML parsing, bulk data transformation, and large-file handling. Use when processing tabular data, spreadsheets, or XML in Python. USE WHEN: user mentions "pandas", "DataFrame", "openpyxl", "read_excel", "lxml", "XPath", "CSV processing", "Excel parsing", "bulk data", "large file", "data transformation", "UTF-16", "codecs" DO NOT USE FOR: SQL databases (use sql-expert), NumPy-only math, ML/training
Create, edit, audit, and extract Excel spreadsheets (.xlsx): generate reports/exports, apply formulas/formatting/charts/data validation, parse existing workbooks, and avoid spreadsheet risks (formula injection, broken links, hidden rows). Supports ExcelJS, openpyxl, pandas, XlsxWriter, and SheetJS.
Expert in automating Excel workflows using Node.js (ExcelJS, SheetJS) and Python (pandas, openpyxl).