584 skills · sorted by relevance
Create, edit, and clean spreadsheet files, including Excel workbooks and CSV data. Add formulas, formatting, and charts, preserve existing workbook conventions, and recalculate formulas with error checks before delivering the spreadsheet.
Create and edit spreadsheets for budgets and editable tables, including targeted cell updates and added records. Save in ODS by default, or use XLSX when Excel compatibility or supported embedded charts are needed.
Create and debug formulas for Excel and Google Sheets, including formulas that return multiple results. Get placement instructions, worked examples, checks for blanks and duplicates, and equivalent formulas when moving between platforms.
Create and process Excel files, PDF checklists, and structured reports by running Python scripts directly. The skill covers multiple sheets, formulas, formatting, data transformations, and error handling for document workflows with several steps.
Process complex Excel files by running Python scripts directly through run_shell. Use pandas for data transformations and openpyxl for workbook editing, including multiple sheets, formulas, and formatting, with explicit saving and error reporting.
Create or edit Excel workbooks with checks for sheet names, row counts, formulas, and merged cells. Reopen the saved file and verify each requirement, recording explicit results rather than relying on a completion summary.
Create and edit Excel workbooks by running a complete Python script through the shell. Covers multiple sheets, data entry, formatting, formulas, and saving files when other file-reading or code-execution tools fail.
Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.
Audit generated Excel reports by reopening saved workbooks, listing populated rows and formulas, and comparing subtotal references with independently identified detail rows. Detect missing or extra rows in totals and preserve an inspection log.
Recover from failed Excel creation or editing by switching from execute_code_sandbox to shell_agent. It guides clear task descriptions so the agent can install missing libraries, run code, retry errors, and confirm file creation.
Handle merged cells before filling Excel templates with openpyxl, a Python library for spreadsheets. This skill shows how to inspect merged ranges, unmerge the required areas, write values, and save the workbook without merged-cell write errors.
Clean Excel data and group records with similar numerical features. Produce a combined view of indicator trends, value distributions, category shares, and grouped data, then export the charts as an image and cleaned records as Excel.
Analyze Excel data using custom categories, count distributions, and compare groups with charts. Score text using its length, technical terms, numbers, and selected complex concepts, then visualize difficulty levels and the relationship between text length and scores.
Filter Excel data using candidate column names, RGB color values, text prefixes, and regular expressions, which match text patterns. Calculate totals and averages, then export results to Excel with highlighted rows and a download link.
Extract coefficients associated with a chosen label across Excel sheets and check them against a standard value. Create a comparison workbook showing each value, its source sheet, and red highlighting for rows that fail the check.
Choose suitable libraries for converting spreadsheet data and image files, or extracting text and tables from documents. Covers supported format pairs and identifies conversions unavailable in the described environment before work begins.
Create, edit, analyze, and format Excel, CSV, and TSV files using Python. Preserves existing spreadsheet styles and formulas, checks references, and supports summaries, charts, and readable layouts for new workbooks.
Build an Excel workbook showing how an acquisition changes earnings per share. Organize purchase price, funding, and synergy assumptions, compare deal scenarios, calculate the synergies needed to avoid reducing earnings per share, and prepare a concise summary.
Create PowerPoint files from Excel financial models using Python. Build slides with figures linked to source cells, apply a firm template, and embed chart images for pitch decks, investment memos, or earnings presentations.
Extracts, converts, or edits selected parts of spreadsheets, Word documents, PDFs, and PowerPoint files. It creates a separate output file, checks that the selection still matches the source, and verifies the saved result without modifying the original.
Builds an Excel model to estimate a company’s equity value from future cash flows. It calculates financing costs, compares three business scenarios, and shows how changes in growth, margins, and other assumptions affect valuation.
Create, edit, and clean spreadsheet files, including Excel workbooks and CSV data. Add formulas, formatting, and charts, preserve existing template styles, and recalculate formulas to check for errors before delivering the spreadsheet.
Gather web information and turn it into an Excel workbook with explicit checks. Handles search failures through delegated research, records sources and missing data, and verifies the saved workbook against requested requirements.
Continue Excel file creation and editing when execute_code_sandbox repeatedly fails with openpyxl errors. Use run_shell to run Python directly, then check that the workbook was saved with the expected sheets and content.