Excel XLSX

Setup

On first use, read setup.md for integration guidelines. Ask user preferences naturally during conversation.

holo-desktop 执行方式

本环境已安装 openpyxl 和 xlsxwriter。生成 Excel 文件的方法：

使用 shell 工具执行 Python 脚本，用 openpyxl 创建 .xlsx 文件。示例：

python -c "
import json, sys
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook()
ws = wb.active
ws.title = '客户清单'

# Header
headers = ['公司名', '国家', 'LinkedIn', '决策人', '职位', '邮箱']
for col, h in enumerate(headers, 1):
    cell = ws.cell(row=1, column=col, value=h)
    cell.font = Font(bold=True, color='FFFFFF')
    cell.fill = PatternFill(start_color='1F4E79', fill_type='solid')

# Data rows (从 JSON 文件读取或内联)
data = json.load(open('reports/input.json'))
for i, row in enumerate(data, 2):
    ws.cell(row=i, column=1, value=row['company'])
    # ... more columns

wb.save('reports/output.xlsx')
print('Saved: reports/output.xlsx')
"

关键点：

• 先用 write_file 把数据写成 JSON → 再用 shell + Python 把 JSON 转成 .xlsx
• 表头加粗、背景色、自动筛选 (ws.auto_filter.ref)
• 数字列右对齐、文本列左对齐
• 完成后告知用户 .xlsx 文件路径

When to Use

User needs to read, write, or generate Excel files (.xlsx, .xls, .xlsm) for tabular/structured data. Agent handles type coercion, date serialization, formula evaluation, and cross-platform quirks.

✅ 使用 Excel（必须生成 .xlsx 文件）

• 客户清单 — 必须 Excel，禁止 JSON/CSV/Markdown
• 报价明细、对比表
• 数字计算、筛选、排序、数据透视
• Pipeline 数据、数据库导出
• 行列结构的结构化数据

❌ 不使用 Excel

• 叙事文本、段落、标题为主的报告 → 用 word-docx 生成 .docx
• 背调报告、市场分析、ICP 分析 → 用 word-docx
• 开发信、商务函件 → 用 word-docx 或对话中展示
• 简短文本（不足 1 页）→ 直接在对话中展示

Architecture

Memory lives in ~/excel-xlsx/. See memory-template.md for structure.

~/excel-xlsx/
└── memory.md     # Preferences, tools, pain points

Quick Reference

Core Rules

1. Dates Are Serial Numbers

Excel stores dates as days since 1900-01-01 (Windows) or 1904-01-01 (Mac legacy). Check workbook date system before converting. Time is fractional: 0.5 = noon, 0.25 = 6 AM.

2. The 1900 Leap Year Bug

Excel incorrectly treats 1900 as a leap year. Serial 60 represents Feb 29, 1900 (invalid date). Account for this when calculating dates before March 1, 1900.

3. 15-Digit Precision Limit

Numbers beyond 15 digits silently truncate. Use TEXT format for: phone numbers, IDs, credit cards, any long numeric identifiers. Leading zeros also require TEXT.

4. Formulas vs Cached Values

Cells may contain both formula and cached result. Some readers return formula string, others return cached value. Force recalculation if cached values might be stale.

5. Merged Cells Are Traps

Only the top-left cell of a merged range holds the value. Reading other cells in the merge returns empty. Hidden rows/columns still contain data.

6. Cross-Platform Testing Required

Windows vs Mac Excel can differ in date system. LibreOffice/Google Sheets may not support all features. Always test roundtrip compatibility when generating files for unknown consumers.

7. Use Streaming for Large Files

Loading large files fully into RAM causes memory issues. Use streaming readers (row-by-row) for files with 100K+ rows. Empty rows at end may be padded by some writers.

Common Traps

• Type inference on read → Numbers stored as text stay text; explicit conversion needed
• Column index confusion → A=0 or A=1 varies by library; always verify convention
• Newlines in cells → \n works but cell needs "wrap text" format to display
• External references → [Book.xlsx]Sheet!A1 breaks when source file moves
• Password protection → Trivial to break; not real security; encrypt file externally if needed
• XLSM files → Contain macros (security risk); XLSB is binary (faster but less compatible)
• Shared strings → Large files reuse text indices; libraries handle this, but be aware

Format Limits

Security & Privacy

Data that stays local:

• All file processing happens locally
• User preferences stored in ~/excel-xlsx/memory.md with consent
• No external services called

This skill does NOT:

• Send data to external endpoints
• Require network access

Related Skills

Install with clawhub install <slug> if user confirms:

• csv — CSV parsing and generation
• data — Data processing patterns
• data-analysis — Analysis workflows

Feedback

• If useful: clawhub star excel-xlsx
• Stay updated: clawhub sync