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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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• Resolve conflicting workbook reports from agents
• Check that spreadsheet edits were saved
• Count rows selected with a marker column

Audit an Excel workbook before editing, then verify the saved file with Python and openpyxl. Each requested requirement receives an explicit status, so completion depends on checks of the actual file.

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• Verify exact sheet names and row counts
• Check sample size and category coverage
• Confirm required source sheets remain after editing

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.

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• Continuing Excel creation after sandbox errors
• Editing existing workbooks and adjusting column widths
• Checking saved workbook sheets and content

当代码涉及 Excel/CSV/JSON/PDF 大文件导出、批量序列化、内存里构建大对象时触发。防止 OOM、临时文件残留、同步导出阻塞 HTTP 线程等内存安全陷阱。

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Produce a .xlsx workbook file on disk for headless sessions or artifact-based workflows instead of driving a live Excel workbook. Use when the user needs a workbook artifact created or updated from data and instructions.

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创建用公式联动利润表、资产负债表和现金流量表的 Excel 模型，分阶段填入历史实际数据与预测假设，比较不同情景，并检查三张报表之间的一致性。

• 向财务模板填入历史实际数据
• 建立三张财务报表联动的预测
• 比较基准、乐观和悲观情景

Build Excel workbooks for buyouts financed with debt. Using a supplied or standard template, the skill connects funding, operating forecasts, debt repayment, and returns, calculating IRR, an annualized return measure, and MOIC, the investment multiple.

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• Populate an LBO template with acquisition assumptions
• Review borrowing, interest, and repayment schedules
• Calculate investment returns using IRR and MOIC

生成Excel文件，估算企业收购对每股收益的影响。整理收购价格、融资和协同效应假设，制作不同条件的比较表，以及用于说明收购影响的摘要。

• 估算收购对每股收益的影响
• 比较现金和股票支付条件
• 比较收购价格与协同效应假设

Turn company documents, public filings, and other sources into structured Excel workbooks for investment review. Organize financial statements and operating metrics, document sources and adjustments, and check that calculations and statements reconcile.

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• Preparing financial data for M&A due diligence
• Building materials for investment committee review
• Standardizing reporting across portfolio companies

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.

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• Clean messy CSV rows and headers into a usable spreadsheet
• Add formulas and charts to an existing Excel workbook
• Build a financial model with editable assumptions

Run a saved weekly or monthly report and combine its results with a brief business snapshot. Deliver one briefing with an XLSX workbook, using a connected data source or uploaded files, and reuse the definition for scheduled runs.

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• Receive the same weekly or monthly report on schedule
• Review report figures alongside cash and sales context
• Rerun a saved report from CSV or XLSX data

Build repeatable business reports from connected data sources or uploaded CSV and XLSX files. Define metrics and comparisons, check the calculations, deliver a concise summary and Excel workbook, and save the report definition for future or scheduled runs.

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• Comparing sales by location with last year
• Reviewing overdue receivables by age
• Tracking labor costs as a percentage of revenue

Define service reliability targets, choose measurements that reflect user experience, and calculate error budgets—the failures a target allows. Generate alert thresholds and review existing definitions for unrealistic targets, unclear metrics, and missing response policies.

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• Defining reliability targets for a new service
• Calculating allowed downtime and alert thresholds
• Reviewing existing reliability definitions

Create and edit spreadsheet files, clean messy tables, and convert tabular formats. Add formulas, formatting, and charts while following existing template styles, then recalculate formulas and check for errors before delivering the spreadsheet.

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• Clean messy CSV data into a spreadsheet
• Add formulas and charts to an Excel workbook
• Update a workbook using its existing formatting

Create, read, edit, and convert presentations, spreadsheets, Word documents, and PDFs with GenOffice's command line. Build files from text or data, inspect existing documents, and render pages as images to review their appearance.

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• Build a presentation from a brief
• Create a workbook with formulas from CSV or JSON
• Turn Markdown into a Word document

Process Excel workbooks by saving Python scripts to files and running them through the shell. Covers multiple sheets, data transformations, formulas, formatting, and error reporting for complex spreadsheet tasks.

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• Transform revenue data and save a processed Excel workbook
• Apply calculations across multiple worksheets
• Format report headers with colors and alignment

Create, edit, and analyze spreadsheets with formulas, formatting, and visualizations. Preserve existing workbook conventions, keep calculations responsive to input changes, and use formula recalculation and error checks to verify the resulting files.

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• Create a spreadsheet with formulas and formatting
• Update an existing workbook while preserving formulas
• Analyze and visualize Excel or CSV data

Clean data across multiple Excel sheets, compare totals between sheets, and summarize categories and proportions. Create charts and export a formatted workbook with unusual values highlighted for review.

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• Comparing totals across Excel sheets
• Cleaning inconsistent text and blank cells
• Charting category counts and proportions

Filter Excel rows using conditions across several numeric columns. Count rows across sheets, convert selected fields to numbers, remove duplicate rows and records with missing identifiers, then export the filtered results to a new workbook.

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• Extract rows where several numeric columns are zero
• Clean numeric fields before filtering
• Remove duplicate rows and missing identifiers

Analyze large Excel workbooks by totaling values by category and identifying the highest result. The workflow can convert data to Parquet, a column-based storage format, and export a styled Excel report with highlighted results.

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• Assessing row counts across workbook sheets
• Converting large datasets to Parquet
• Finding the category with the highest total

Create and edit spreadsheet files, clean messy tables, and convert tabular formats. Add formulas, formatting, and charts while following existing template styles, then recalculate formulas and check for errors before delivering the spreadsheet.

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• Clean messy CSV data into a spreadsheet
• Add formulas and charts to an Excel workbook
• Update a workbook using its existing formatting

Extract unidentified external addresses from TRES Finance and export a deduplicated Excel workbook. An import-ready contacts sheet lets users add names and tags, while a reference sheet shows inferred networks, transaction counts, and USD volumes to help prioritize labeling.

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• Building an address book from transaction history
• Preparing a TRES contacts import sheet
• Prioritizing unidentified addresses by transaction volume

Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management. Use for creating Application Insights components, web tests, workbooks, analytics items, and API keys. Triggers: "Application Insights", "ApplicationInsights", "App Insights", "APM", "application monitoring", "web tests", "availability tests", "workbooks".

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Create, edit, analyze, or convert Excel spreadsheets (.xlsx, .xlsm, .xltx) where the workbook file is the primary deliverable. Use for formulas, formatting, financial models, multi-sheet workbooks, and tabular cleanup exported to Excel. Also applies to .csv/.tsv when the user wants spreadsheet output. Do NOT use for Word documents, HTML reports, standalone Python scripts, database pipelines, or Google Sheets API work.

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