Skills2026年3月29日·1 分钟阅读

Claude Official Skill: xlsx

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, ...

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快速使用

先拿来用,再决定要不要深挖

这里应该同时让用户和 Agent 知道第一步该复制什么、安装什么、落到哪里。

# Install via Claude Code
claude skill install anthropics/skills/xlsx

Or manually: copy the SKILL.md content below to .claude/skills/xlsx/SKILL.md


介绍

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, .... Official skill from Anthropic's skills repository — maintained by the Claude Code team.


Skill Content

Requirements for Outputs

All Excel files

Professional Font

  • Use a consistent, professional font (e.g., Arial, Times New Roman) for all deliverables unless otherwise instructed by the user

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 Requirements for Hardcodes

  • Comment or in cells beside (if end of table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]"
  • Examples:
    • "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

Important Requirements

LibreOffice Required for Formula Recalculation: You can assume LibreOffice is installed for recalculating formula values using the scripts/recalc.py script. The script automatically configures LibreOffice on first run, including in sandboxed environments where Unix sockets are restricted (handled by scripts/office/soffice.py)

Reading and analyzing data

Data analysis with pandas

For data analysis, visualization, and basic operations, use pandas which provides powerful data manipulation capabilities:

import pandas as pd

# Read Excel
df = pd.read_excel('file.xlsx')  # Default: first sheet
all_sheets = pd.read_excel('file.xlsx', sheet_name=None)  # All sheets as dict

# Analyze
df.head()      # Preview data
df.info()      # Column info
df.describe()  # Statistics

# Write Excel
df.to_excel('output.xlsx', index=False)

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.

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来源与感谢

Author: Anthropic Repository: anthropics/skills Skill: xlsx License: MIT

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