office-mastery

name	office-mastery
description	Complete office skills: Word, Excel, PPT, PDF processing with Python libraries and MCP servers
version	1.0.0
author	Hermes Agent
license	MIT
platforms	["linux","macos","windows"]
metadata	{"hermes":{"tags":["office","word","excel","ppt","pdf","productivity","documents"],"related_skills":["powerpoint","nano-pdf","ocr-and-documents","native-mcp"]}}

Office Mastery Skill

Comprehensive office document processing skills for Word, Excel, PowerPoint, and PDF files using Python libraries and MCP servers.

When to Use

Use this skill whenever you need to:

• Create, read, edit, or convert Word documents (.docx)
• Process Excel spreadsheets (.xlsx, .xls) with formulas, charts,数据分析
• Create professional PowerPoint presentations (.pptx)
• Handle PDF files: extract text, merge, split, convert
• Automate office workflows and document generation
• Process academic papers, reports, contracts, and formal documents

Quick Reference

Task	Tool/Library	Command/Method
Word processing	python-docx	pip install python-docx
Excel processing	openpyxl	pip install openpyxl
PowerPoint	python-pptx	pip install python-pptx
PDF processing	PyPDF2, pdfplumber	pip install PyPDF2 pdfplumber
Document conversion	pandoc	sudo apt install pandoc
OCR processing	tesseract, pytesseract	sudo apt install tesseract-ocr

Word Document Processing

Core Library: python-docx

from docx import Document
from docx.shared import Inches, Pt, RGBColor
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.enum.style import WD_STYLE_TYPE

# Create new document
doc = Document()

# Add heading
doc.add_heading('公文标题', 0)

# Add paragraph with formatting
paragraph = doc.add_paragraph()
run = paragraph.add_run('正文内容')
run.font.size = Pt(12)
run.font.name = '宋体'

# Add table
table = doc.add_table(rows=3, cols=3)
table.style = 'Table Grid'

# Save document
doc.save('output.docx')

Word MCP Server (Recommended)

# Add to ~/.hermes/config.yaml
mcp_servers:
  word:
    command: "npx"
    args: ["-y", "@gongrzhe/office-word-mcp-server"]
    timeout: 60

Available Tools:

• mcp_word_create_document - Create new Word document
• mcp_word_add_heading - Add headings with levels
• mcp_word_add_paragraph - Add formatted paragraphs
• mcp_word_add_table - Add tables with data
• mcp_word_add_image - Insert images
• mcp_word_search_and_replace - Find and replace text
• mcp_word_get_comments - Extract comments
• mcp_word_accept_all_revisions - Accept tracked changes

Document Formatting Best Practices

# Chinese document formatting
def format_chinese_document(doc):
    # Set default font
    style = doc.styles['Normal']
    font = style.font
    font.name = '宋体'
    font.size = Pt(12)
    
    # Set paragraph spacing
    paragraph_format = style.paragraph_format
    paragraph_format.space_after = Pt(0)
    paragraph_format.line_spacing = 1.5
    
    # Add page margins
    for section in doc.sections:
        section.top_margin = Inches(1)
        section.bottom_margin = Inches(1)
        section.left_margin = Inches(1.25)
        section.right_margin = Inches(1.25)

Track Changes and Comments

# Read tracked changes
from docx import Document
doc = Document('document_with_changes.docx')

# Access comments
for comment in doc.part.comments:
    print(f"Comment by {comment.author}: {comment.text}")

Excel Processing

Core Library: openpyxl

from openpyxl import Workbook, load_workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.chart import BarChart, Reference
from openpyxl.utils import get_column_letter

# Create new workbook
wb = Workbook()
ws = wb.active

# Add data
ws['A1'] = '姓名'
ws['B1'] = '成绩'
ws['A2'] = '张三'
ws['B2'] = 85

# Apply formatting
header_font = Font(bold=True, color="FFFFFF")
header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")

for cell in ws[1]:
    cell.font = header_font
    cell.fill = header_fill

# Add chart
chart = BarChart()
chart.title = "成绩统计"
data = Reference(ws, min_col=2, min_row=1, max_row=10)
cats = Reference(ws, min_col=1, min_row=2, max_row=10)
chart.add_data(data, titles_from_data=True)
chart.set_categories(cats)
ws.add_chart(chart, "D2")

# Save
wb.save('output.xlsx')

Excel MCP Server

# Add to ~/.hermes/config.yaml
mcp_servers:
  excel:
    command: "npx"
    args: ["-y", "@haris-musa/excel-mcp-server"]
    timeout: 60

Available Tools:

• mcp_excel_read_worksheet - Read data from worksheet
• mcp_excel_write_worksheet - Write data to worksheet
• mcp_excel_create_chart - Create charts and graphs
• mcp_excel_format_cells - Apply formatting
• mcp_excel_create_pivot_table - Create pivot tables
• mcp_excel_apply_formula - Apply Excel formulas

Data Analysis with Excel

import pandas as pd
from openpyxl import Workbook

# Read Excel data
df = pd.read_excel('data.xlsx', sheet_name='Sheet1')

# Data analysis
summary = df.groupby('类别').agg({
    '销售额': ['sum', 'mean', 'count'],
    '利润': 'sum'
}).round(2)

# Export to Excel with multiple sheets
with pd.ExcelWriter('analysis.xlsx', engine='openpyxl') as writer:
    summary.to_excel(writer, sheet_name='汇总')
    df.to_excel(writer, sheet_name='原始数据', index=False)

PowerPoint Processing

Core Library: python-pptx

from pptx import Presentation
from pptx.util import Inches, Pt
from pptx.dml.color import RGBColor
from pptx.enum.text import PP_ALIGN

# Create presentation
prs = Presentation()

# Add title slide
slide_layout = prs.slide_layouts[0]
slide = prs.slides.add_slide(slide_layout)
title = slide.shapes.title
subtitle = slide.placeholders[1]

title.text = "演示文稿标题"
subtitle.text = "副标题"

# Add content slide
slide_layout = prs.slide_layouts[1]
slide = prs.slides.add_slide(slide_layout)
title = slide.shapes.title
body = slide.placeholders[1]

title.text = "内容标题"
tf = body.text_frame
tf.text = "第一点"
tf.add_paragraph().text = "第二点"

# Save
prs.save('output.pptx')

Advanced Presentation Design

from pptx import Presentation
from pptx.util import Inches, Pt, Emu
from pptx.dml.color import RGBColor
from pptx.enum.shapes import MSO_SHAPE

def create_professional_slide():
    prs = Presentation()
    prs.slide_width = Inches(13.333)
    prs.slide_height = Inches(7.5)
    
    # Add background
    slide = prs.slides.add_slide(prs.slide_layouts[6])  # Blank layout
    background = slide.background
    fill = background.fill
    fill.solid()
    fill.fore_color.rgb = RGBColor(0x1E, 0x27, 0x61)  # Navy blue
    
    # Add title
    left = Inches(1)
    top = Inches(1)
    width = Inches(11)
    height = Inches(1.5)
    title_box = slide.shapes.add_textbox(left, top, width, height)
    title_frame = title_box.text_frame
    title_frame.text = "专业演示文稿"
    
    # Format title
    for paragraph in title_frame.paragraphs:
        paragraph.font.size = Pt(44)
        paragraph.font.bold = True
        paragraph.font.color.rgb = RGBColor(0xFF, 0xFF, 0xFF)
        paragraph.alignment = PP_ALIGN.CENTER
    
    # Add content
    left = Inches(1)
    top = Inches(3)
    width = Inches(11)
    height = Inches(3)
    content_box = slide.shapes.add_textbox(left, top, width, height)
    content_frame = content_box.text_frame
    
    points = ["要点一：重要信息", "要点二：详细说明", "要点三：总结"]
    for point in points:
        p = content_frame.add_paragraph()
        p.text = point
        p.font.size = Pt(24)
        p.font.color.rgb = RGBColor(0xFF, 0xFF, 0xFF)
        p.space_after = Pt(12)
    
    return prs

PowerPoint MCP Server

# Add to ~/.hermes/config.yaml
mcp_servers:
  pptx:
    command: "npx"
    args: ["-y", "@mcp-ms-office-documents"]
    timeout: 60

PDF Processing

Core Libraries

# PyPDF2 for basic operations
from PyPDF2 import PdfReader, PdfWriter, PdfMerger

# Read PDF
reader = PdfReader("input.pdf")
text = ""
for page in reader.pages:
    text += page.extract_text()

# Merge PDFs
merger = PdfMerger()
merger.append("file1.pdf")
merger.append("file2.pdf")
merger.write("merged.pdf")
merger.close()

# Split PDF
reader = PdfReader("input.pdf")
writer = PdfWriter()
writer.add_page(reader.pages[0])
writer.write("first_page.pdf")

Advanced PDF Processing with pdfplumber

import pdfplumber

# Extract tables from PDF
with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            for row in table:
                print(row)

# Extract text with layout
with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text(layout=True)
        print(text)

PDF MCP Servers

# Add to ~/.hermes/config.yaml
mcp_servers:
  pdf:
    command: "npx"
    args: ["-y", "@sylphx-ai/pdf-reader-mcp"]
    timeout: 60
  
  ebook:
    command: "npx"
    args: ["-y", "@onebirdrocks/ebook-mcp"]
    timeout: 60

Document Conversion

# Install pandoc for document conversion
sudo apt install pandoc

# Convert Word to PDF
pandoc input.docx -o output.pdf

# Convert PDF to Word (limited)
pandoc input.pdf -o output.docx

# Convert Markdown to Word
pandoc input.md -o output.docx --reference-doc=template.docx

MCP Server Configuration

Recommended Free MCP Servers for Office

# ~/.hermes/config.yaml
mcp_servers:
  # Word document processing
  word:
    command: "npx"
    args: ["-y", "@gongrzhe/office-word-mcp-server"]
    timeout: 60
  
  # Excel processing
  excel:
    command: "npx"
    args: ["-y", "@haris-musa/excel-mcp-server"]
    timeout: 60
  
  # PDF processing
  pdf:
    command: "npx"
    args: ["-y", "@sylphx-ai/pdf-reader-mcp"]
    timeout: 60
  
  # Document intelligence
  kreuzberg:
    command: "npx"
    args: ["-y", "@kreuzberg-dev/kreuzberg"]
    timeout: 120
  
  # Microsoft 365 integration
  ms365:
    command: "npx"
    args: ["-y", "@softeria/ms-365-mcp-server"]
    timeout: 60
  
  # File system access
  filesystem:
    command: "npx"
    args: ["-y", "@modelcontextprotocol/server-filesystem", "/home/admin/documents"]
    timeout: 30
  
  # Time server
  time:
    command: "uvx"
    args: ["mcp-server-time"]
    timeout: 30

Academic and Student Skills

Research Paper Processing

# Extract references from PDF
import re
from PyPDF2 import PdfReader

def extract_references(pdf_path):
    reader = PdfReader(pdf_path)
    text = ""
    for page in reader.pages:
        text += page.extract_text()
    
    # Find references section
    ref_pattern = r'References\s*(.*?)(?:\n\n|\Z)'
    match = re.search(ref_pattern, text, re.DOTALL | re.IGNORECASE)
    
    if match:
        references = match.group(1)
        # Split individual references
        ref_list = re.split(r'\n\s*\d+\.', references)
        return [ref.strip() for ref in ref_list if ref.strip()]
    
    return []

Academic Formatting

from docx import Document
from docx.shared import Pt, Inches
from docx.enum.text import WD_ALIGN_PARAGRAPH

def create_academic_paper():
    doc = Document()
    
    # Title
    title = doc.add_heading('论文标题', 0)
    title.alignment = WD_ALIGN_PARAGRAPH.CENTER
    
    # Abstract
    doc.add_heading('摘要', level=1)
    abstract = doc.add_paragraph()
    abstract.add_run('本文研究了...').font.size = Pt(12)
    
    # Keywords
    keywords = doc.add_paragraph()
    keywords.add_run('关键词：').bold = True
    keywords.add_run('关键词1；关键词2；关键词3')
    
    # Sections
    doc.add_heading('1. 引言', level=1)
    doc.add_paragraph('研究背景和意义...')
    
    doc.add_heading('2. 文献综述', level=1)
    doc.add_paragraph('相关研究...')
    
    # References
    doc.add_heading('参考文献', level=1)
    refs = ['[1] 作者. 标题. 期刊, 年份.', '[2] 作者. 标题. 期刊, 年份.']
    for ref in refs:
        doc.add_paragraph(ref, style='List Number')
    
    return doc

Data Analysis for Students

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

def student_data_analysis():
    # Sample data
    data = {
        '科目': ['数学', '英语', '物理', '化学', '生物'],
        '成绩': [85, 92, 78, 88, 95],
        '学分': [4, 3, 3, 3, 2]
    }
    
    df = pd.DataFrame(data)
    
    # Calculate GPA
    df['绩点'] = df['成绩'].apply(lambda x: x / 10 - 5 if x >= 60 else 0)
    df['加权绩点'] = df['绩点'] * df['学分']
    
    gpa = df['加权绩点'].sum() / df['学分'].sum()
    
    # Create visualization
    plt.figure(figsize=(10, 6))
    plt.bar(df['科目'], df['成绩'], color='skyblue')
    plt.title('各科成绩统计')
    plt.xlabel('科目')
    plt.ylabel('成绩')
    plt.ylim(0, 100)
    
    # Add value labels
    for i, v in enumerate(df['成绩']):
        plt.text(i, v + 1, str(v), ha='center', va='bottom')
    
    plt.tight_layout()
    plt.savefig('成绩统计.png', dpi=300)
    plt.show()
    
    return df, gpa

Automation Scripts

Batch Document Processing

import os
from pathlib import Path
from docx import Document

def batch_process_documents(input_dir, output_dir):
    """Batch process Word documents"""
    input_path = Path(input_dir)
    output_path = Path(output_dir)
    output_path.mkdir(exist_ok=True)
    
    for doc_file in input_path.glob('*.docx'):
        try:
            doc = Document(doc_file)
            
            # Process document
            for paragraph in doc.paragraphs:
                if '旧文本' in paragraph.text:
                    paragraph.text = paragraph.text.replace('旧文本', '新文本')
            
            # Save processed document
            output_file = output_path / doc_file.name
            doc.save(output_file)
            print(f"Processed: {doc_file.name}")
            
        except Exception as e:
            print(f"Error processing {doc_file.name}: {e}")

Report Generation

from docx import Document
from docx.shared import Inches, Pt
from datetime import datetime
import pandas as pd

def generate_monthly_report(data_file, template_file, output_file):
    """Generate monthly report from data"""
    
    # Load data
    df = pd.read_excel(data_file)
    
    # Create document from template
    doc = Document(template_file)
    
    # Add current date
    date_paragraph = doc.add_paragraph()
    date_paragraph.add_run(f"报告日期：{datetime.now().strftime('%Y年%m月%d日')}")
    
    # Add summary table
    table = doc.add_table(rows=1, cols=3)
    table.style = 'Table Grid'
    
    # Header
    header_cells = table.rows[0].cells
    header_cells[0].text = '项目'
    header_cells[1].text = '数量'
    header_cells[2].text = '金额'
    
    # Data rows
    for _, row in df.iterrows():
        row_cells = table.add_row().cells
        row_cells[0].text = str(row['项目'])
        row_cells[1].text = str(row['数量'])
        row_cells[2].text = f"¥{row['金额']:,.2f}"
    
    # Save
    doc.save(output_file)

Verified MCP Configuration (tested on Alibaba Cloud Linux 3, Python 3.11, Node 22)

# ~/.hermes/config.yaml — add under mcp_servers:
mcp_servers:
  word:
    command: "npx"
    args: ["-y", "@gongrzhe/office-word-mcp-server"]
    timeout: 60
  excel:
    command: "npx"
    args: ["-y", "@haris-musa/excel-mcp-server"]
    timeout: 60
  pdf:
    command: "npx"
    args: ["-y", "@sylphx-ai/pdf-reader-mcp"]
    timeout: 60
  kreuzberg:
    command: "npx"
    args: ["-y", "@kreuzberg-dev/kreuzberg"]
    timeout: 120
  filesystem:
    command: "npx"
    args: ["-y", "@modelcontextprotocol/server-filesystem", "/home/admin"]
    timeout: 30
  time:
    command: "uvx"
    args: ["mcp-server-time"]
    timeout: 30

Tools register as mcp_word_*, mcp_excel_*, mcp_pdf_*, mcp_kreuzberg_*, mcp_filesystem_*, mcp_time_*.

Dependencies Installation

Dependencies Installation

⚠️ Python Environment Pitfall

The server has two Python versions:

• System Python 3.6 (/usr/bin/python3) — pip3 installs HERE
• Hermes venv Python 3.11 (~/.hermes/hermes-agent/venv/bin/python3) — the active python3

Always use python3 -m pip instead of pip3 to install into the correct environment:

# ✅ Correct — installs into Python 3.11 venv
python3 -m pip install python-docx openpyxl python-pptx PyPDF2 pdfplumber reportlab pandas matplotlib seaborn

# ❌ Wrong — installs into system Python 3.6
pip3 install python-docx

For Chinese Cloud Linux (Alibaba Cloud Linux 3), install system deps first for Pillow/matplotlib:

sudo yum install -y zlib-devel libjpeg-turbo-devel libpng-devel freetype-devel

Standard Install

# Core office libraries
python3 -m pip install python-docx openpyxl python-pptx PyPDF2 pdfplumber reportlab

# Data analysis + visualization
python3 -m pip install pandas matplotlib seaborn numpy

# Document conversion
sudo yum install pandoc  # or: sudo apt install pandoc

# OCR support (optional)
sudo yum install tesseract-ocr
python3 -m pip install pytesseract pillow

## Cleanup After Use

**User preference**: Always clean up test/demo files after creating them. Do NOT leave generated .docx/.xlsx/.pptx/.pdf/.csv/.png files in the working directory. If files were copied to the cloud disk (AList at /opt/aivos-disk/storage/), clean those too unless user explicitly wants to keep them.

```bash
# After demo/testing, remove generated files
rm -f *.docx *.xlsx *.pptx *.pdf *.csv *.png
# Also clean cloud disk copies
rm -f /opt/aivos-disk/storage/*演示* /opt/aivos-disk/storage/*测试*

QA and Testing

Document Validation

from docx import Document
import openpyxl
from pptx import Presentation

def validate_documents():
    """Validate office documents"""
    
    # Test Word document
    try:
        doc = Document('test.docx')
        print(f"Word document: {len(doc.paragraphs)} paragraphs")
    except Exception as e:
        print(f"Word document error: {e}")
    
    # Test Excel file
    try:
        wb = openpyxl.load_workbook('test.xlsx')
        print(f"Excel workbook: {len(wb.sheetnames)} sheets")
    except Exception as e:
        print(f"Excel error: {e}")
    
    # Test PowerPoint
    try:
        prs = Presentation('test.pptx')
        print(f"PowerPoint: {len(prs.slides)} slides")
    except Exception as e:
        print(f"PowerPoint error: {e}")

Best Practices

1. Always use templates - Create document templates for consistent formatting
2. Backup original files - Never modify original documents directly
3. Validate input data - Check data integrity before processing
4. Use appropriate libraries - Choose the right tool for each task
5. Handle errors gracefully - Implement proper error handling
6. Optimize for performance - Use streaming for large files
7. Maintain version control - Track document changes
8. Follow accessibility standards - Ensure documents are accessible

Common Issues and Solutions

Issue: Chinese characters not displaying

Solution: Set font encoding and use appropriate Chinese fonts

Issue: Large files causing memory issues

Solution: Use streaming processing and chunked reading

Issue: Formatting lost during conversion

Solution: Use specialized conversion tools and validate output

Issue: MCP server connection failures

Solution: Check network connectivity and server status

This comprehensive skill covers all major office document processing needs, from basic operations to advanced automation and MCP integration.