By name: xlsx description: >- 全面的 電子表格 creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. 當需要 to work with 電子表格s (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new 電子表格s with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing 電子表格s while preserving formulas, (4) Data analysis and visualization in 電子表格s, or (5) Recalculating formulas trigger: when_needed language: zh-TW adapted_from: openskills/xlsx version: 1.0.0-antigravity original_license: Proprietary. LICENSE.txt has complete terms
XLSX 處理指南
技能版本: v1.0 (Antigravity 適配版)
原始來源: openskills/xlsx
語言: 繁體中文
概述
全面的 電子表格 creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. 當需要 to work with 電子表格s (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new 電子表格s with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing 電子表格s while preserving formulas, (4) Data analysis and visualization in 電子表格s, or (5) Recalculating formulas
需求 for Outputs
使用情境
此技能適用於以下情況：
- 用戶明確要求相關功能時
- 任務需要專業領域知識時
- 需要遵循特定工作流程時
All Excel files
Zero Formula Errors
- Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)
Preserve Existing Templates (when updating templates)
- Study and EXACTLY match existing format, style, and conventions when modifying files
- Never impose standardized formatting on files with established patterns
- Existing template conventions ALWAYS override these guidelines
Financial models
Color Coding Standards
Unless otherwise stated by the user or existing template
Industry-Standard Color Conventions
- Blue text (RGB: 0,0,255): Hardcoded inputs, and numbers users will change for scenarios
- Black text (RGB: 0,0,0): ALL formulas and calculations
- Green text (RGB: 0,128,0): Links pulling from other worksheets within same workbook
- Red text (RGB: 255,0,0): External links to other files
- Yellow background (RGB: 255,255,0): Key assumptions needing attention or cells that need to be updated
Number Formatting Standards
Required Format Rules
- Years: Format as text strings (e.g., "2024" not "2,024")
- Currency: Use $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")
- Zeros: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")
- Percentages: Default to 0.0% format (one decimal)
- Multiples: Format as 0.0x for valuation multiples (EV/EBITDA, P/E)
- Negative numbers: Use parentheses (123) not minus -123
Formula Construction Rules
Assumptions Placement
- Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells
- Use cell references instead of hardcoded values in formulas
- Example: Use =B5*(1+$B$6) instead of =B5*1.05
Formula Error Prevention
- Verify all cell references are correct
- Check for off-by-one errors in ranges
- Ensure consistent formulas across all projection periods
- Test with edge cases (zero values, negative numbers)
- Verify no unintended circular references
Documentation 需求 for Hardcodes
- Comment or in cells beside (if end of table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]"
- 範例:
- "Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]"
- "Source: Company 10-Q, Q2 2025, Exhibit 99.1, [SEC EDGAR URL]"
- "Source: Bloomberg Terminal, 8/15/2025, AAPL US Equity"
- "Source: FactSet, 8/20/2025, Consensus Estimates Screen"
XLSX creation, editing, and analysis
概述
A user may ask you to create, edit, or analyze the contents of an .xlsx file. You have different tools and workflows available for different tasks.
Important 需求
LibreOffice Required for Formula Recalculation: You can assume LibreOffice is installed for recalculating formula values using the recalc.py script. The script automatically configures LibreOffice on first run
Reading and analyzing data
Data analysis with pandas
For data analysis, visualization, and basic operations, use pandas which provides powerful data manipulation capabilities:
詳細內容請參閱：example_3.py
Excel File Workflows
CRITICAL: Use Formulas, Not Hardcoded Values
Always use Excel formulas instead of calculating values in Python and hardcoding them. This ensures the spreadsheet remains dynamic and updateable.
❌ WRONG - Hardcoding Calculated Values
詳細內容請參閱：example_4.py
✅ CORRECT - Using Excel Formulas
詳細內容請參閱：example_5.py
This applies to ALL calculations - totals, percentages, ratios, differences, etc. The spreadsheet should be able to recalculate when source data changes.
Common Workflow
- Choose tool: pandas for data, openpyxl for formulas/formatting
- Create/Load: Create new workbook or load existing file
- Modify: Add/edit data, formulas, and formatting
- Save: Write to file
- Recalculate formulas (MANDATORY IF USING FORMULAS): Use the recalc.py script
python recalc.py output.xlsx
詳細內容請參閱：example_6.txt
Editing existing Excel files
詳細內容請參閱：example_7.py
Recalculating formulas
Excel files created or modified by openpyxl contain formulas as strings but not calculated values. Use the provided recalc.py script to recalculate formulas:
python recalc.py <excel_file> [timeout_seconds]
Example:
python recalc.py output.xlsx 30
詳細內容請參閱：[example_8.txt](examples/example_8.txt)
## 最佳實踐
### Library Selection
- **pandas**: Best for data analysis, bulk operations, and simple data export
- **openpyxl**: Best for complex formatting, formulas, and Excel-specific features
### Working with openpyxl
- Cell indices are 1-based (row=1, column=1 refers to cell A1)
- Use `data_only=True` to read calculated values: `load_workbook('file.xlsx', data_only=True)`
- **Warning**: If opened with `data_only=True` and saved, formulas are replaced with values and permanently lost
- For large files: Use `read_only=True` for reading or `write_only=True` for writing
- Formulas are preserved but not evaluated - use recalc.py to update values
### Working with pandas
- Specify data types to avoid inference issues: `pd.read_excel('file.xlsx', dtype={'id': str})`
- For large files, read specific columns: `pd.read_excel('file.xlsx', usecols=['A', 'C', 'E'])`
- Handle dates properly: `pd.read_excel('file.xlsx', parse_dates=['date_column'])`
## Code Style Guidelines
**IMPORTANT**: When generating Python code for Excel operations:
- Write minimal, concise Python code without unnecessary comments
- Avoid verbose variable names and redundant operations
- Avoid unnecessary print statements
**For Excel files themselves**:
- Add comments to cells with complex formulas or important assumptions
- Document data sources for hardcoded values
- Include notes for key calculations and model sections
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## 專案整合
此技能已適配 Antigravity 系統：
- 遵循 `skills/_base/coding_style.md` 編碼規範
- 與 `skills/_base/architecture.md` 架構模式一致
- 符合 Constitution v3.1 語言規範 (繁體中文)
### 相關技能
可搭配以下技能使用：
- `systematic-debugging` - 系統化除錯
- `verification-before-completion` - 完成前驗證