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Work with PDFs to extract text, tables, and images, combine or split documents, rotate pages, and create new files. The guide also covers forms, watermarks, password protection, and OCR, which recognizes text in scanned pages.
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Run linear or logistic regression on CSV or Excel tables to examine relationships between variables. Get coefficients, measures of model fit, significance tests, and checks for overlapping predictors, with explanations in plain language.
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Load, clean, summarize, and join tabular data from CSV, Excel, JSON, or database exports using pandas. Check missing values, data types, and row counts, then independently verify key figures before reporting numbers printed by the code.
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Generate and parse Excel spreadsheets with ExcelJS — create workbooks with multiple sheets, styled cells, formulas, charts, images, and conditional formatting. Use when tasks involve exporting application data to .xlsx, building financial reports, parsing uploaded spreadsheets, or creating data import/export pipelines.
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Read, transform, analyze, and generate Excel and CSV files. Use when a user asks to open a spreadsheet, process Excel data, merge CSVs, create pivot tables, clean up data, convert between Excel and CSV, add formulas, filter rows, or generate reports from tabular data. Handles .xlsx, .xls, and .csv.
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Select random winners from lists, CSV files, Excel, or Google Sheets. Choose multiple winners without duplicates, exclude previous winners, apply entry-based weighting, and record the selection method and timestamp for review.
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Create, edit, and inspect spreadsheets for reusable budgets, models, and trackers. Check formulas and dependent totals, preserve unrelated data, and deliver an editable workbook or a link to the updated native spreadsheet.
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Helps build Python workflows for translating Word, PDF, Excel, PowerPoint, and other documents while preserving formatting. Covers Azure batch translation, multiple target languages, terminology glossaries, and checks for job progress and document errors.
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Build a prioritized list of potential buyers for a company sale. Assess corporate acquirers and investment funds by business fit, financial capacity, and acquisition activity, then organize leading candidates and contact plans in Excel.
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Estimate private equity deal returns across purchase prices, borrowing levels, growth assumptions, exit prices, and holding periods. Produce Excel sensitivity tables showing annualized returns and investment multiples, plus scenario comparisons and a one-page investment committee summary.
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Extract text, tables, and images from PDFs; merge, split, rotate, or create documents; and fill forms. The skill also covers password protection and optical character recognition, which reads text from scanned pages to make documents searchable.
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Turn CSV or tabular data into an Excel dashboard with formula-driven key performance indicators, linked charts, small in-cell trend charts, and conditional formatting. A dedicated opening sheet brings the main figures and visual summaries together.
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Convert office documents, spreadsheets, presentations, ebooks, and PDFs into Markdown text that an agent can read. Save large conversions to a file and use hosted text recognition for scanned PDF pages when needed.
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Convert office documents, spreadsheets, presentations, ebooks, and text-based PDFs into GitHub-Flavored Markdown, a plain-text format supporting tables. Make otherwise unreadable source files available for an agent to read and use in a task.
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Select random winners from lists, CSV files, Excel, or Google Sheets. Choose multiple winners without duplicates, exclude previous winners, apply entry-based weighting, and record the selection method and timestamp for review.
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Recover failed Python tasks by saving the code as a script and running it through the system shell. The workflow covers spreadsheet generation, data processing, output verification, and troubleshooting missing packages, paths, or permissions.
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Run Python code directly on the host when repeated e2b sandbox failures block execution. The skill explains saving scripts, launching them through the shell, and checking outputs when an isolated environment is unnecessary.
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Verify saved Excel files directly with Python and openpyxl, a workbook library. Check sheets, headers, row counts, marked rows, and output files to resolve conflicting agent reports and summarize what actually exists on disk.
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Extract data from supplied spreadsheets and documents, check for missing or truncated content, and try alternative reading methods when needed. Results identify source files and clearly separate extracted facts from external information or estimates.
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Create spreadsheets, diagrams, and PDF reports in a staged workflow. Allocate execution attempts across deliverables, check generated files, and use simpler methods or alternative formats when tool errors or limited remaining attempts interrupt progress.
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Run Python through a saved script when execute_code_sandbox or shell_agent repeatedly fails. The workflow writes code to a file, executes it through run_shell, and checks errors and expected outputs such as spreadsheets or documents.
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Continue file reading and data processing when execute_code_sandbox or read_file fails. This skill runs multiline Python through run_shell, with examples for text, JSON, spreadsheets, PDF and Word documents, plus basic summaries and grouped calculations.
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Create formula-based Excel valuation workbooks for public companies using discounted cash flow, a method that converts future cash flows into present value. Include per-share estimates, assumption sensitivities, source records, and checks that flag model limitations.
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Assess numeric Excel columns using IQR, a measure of the middle half of values, to flag outliers. Summarize counts and limits, create box plots, and examine distribution shape to inform data cleaning.
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