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name: pdf description: Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale. license: Proprietary. LICENSE.txt has complete terms metadata: version: "1.0.0"

PDF文档处理专家 Real Skill

一句话说明

全面的 PDF 文档处理工具，支持文本表格提取、PDF 创建、文档操作和表单填写。

PDF Processing Guide - Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms.

使用场景

适用：

从 PDF 提取文本、表格数据并导出 Excel
创建新的 PDF 文档（报告、证书、发票）
合并、拆分、旋转 PDF 文档
填写 PDF 表单（政府表单、申请表）
批量处理多个 PDF 文件

不适用：

扫描版 PDF（需先 OCR 处理 / requires OCR first）
复杂的 PDF 编辑（用专业软件 / use professional software）

核心流程

用户需求 → 判断任务类型 → 选择工具 → 执行操作 → 验证输出
User request → Task type classification → Tool selection → Execute → Validate

任务类型判断 (Task Classification)：

Extracting Data (提取数据)

文本提取 (Text extraction) → pdfplumber.extract_text()
Better accuracy than pypdf for text extraction
表格提取 (Table extraction) → pdfplumber.extract_tables() + pandas
Intelligent table structure recognition
Export to Excel, CSV, JSON

Creating PDFs (创建 PDF)

简单文档 (Simple documents) → reportlab.pdfgen.canvas
Quick document creation with text and graphics
复杂布局 (Complex layouts) → reportlab.platypus
Paragraphs, Tables, Images with advanced styling

PDF Operations (PDF 操作)

合并 (Merge) → pypdf.PdfWriter
Combine multiple PDFs into one
拆分 (Split) → pypdf.PdfWriter (save each page separately)
旋转 (Rotate) → page.rotate()
元信息 (Metadata) → pypdf.PdfReader.metadata / PdfWriter.add_metadata()

Form Processing (表单处理)

查看字段 (View fields) → See forms.md
填写表单 (Fill forms) → See forms.md
批量处理 (Batch processing) → Loop + form filling API

任务完成标准

必须满足（缺一不可）：

PDF 文件可正常打开
提取的数据完整准确
表格结构保留正确（行列对应）
创建的 PDF 内容清晰可读

质量评级：

⭐⭐⭐⭐⭐ 优秀 - 数据完整 + 格式规范 + 自动化批处理
⭐⭐⭐ 及格 - 数据正确 + PDF 可用
⭐ 失败 - 数据缺失或 PDF 损坏

参考资料（供 AI 使用）

类型	路径	说明
核心文档	`docs/00-SKILL-完整处理指南.md`	Complete PDF processing guide (~300 lines)
表单处理	`docs/forms.md`	PDF form filling detailed tutorial
高级参考	`docs/reference.md`	JavaScript libraries and advanced features

关键原则（AI 必读 / Critical Principles）

1. Prefer pdfplumber for Extraction (优先使用 pdfplumber)

文本提取: More accurate than pypdf
表格识别: Strong table recognition capability
布局保留: Preserves layout information
复杂 PDF: Better for complex PDF processing

2. Table Data Normalization (表格数据规范化)

python

# Best practice for table extraction
import pdfplumber
import pandas as pd
all_tables = []
with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            if table:  # Check not empty
                df = pd.DataFrame(table[1:], columns=table[0])  # First row as header
                all_tables.append(df)
# Combine and clean
combined = pd.concat(all_tables, ignore_index=True)
combined.to_excel("output.xlsx", index=False)

3. Scanned PDFs Require OCR (扫描版需要 OCR)

识别: If text extraction returns empty or garbled text
处理: Must use OCR tools first (Tesseract, Adobe Acrobat, etc.)
告知用户: Clearly inform user that OCR pre-processing is needed

4. Memory Management for Large Files (大文件内存管理)

Batch processing for multiple PDFs
Process pages sequentially rather than loading entire document
Use generators when possible

快速命令参考 (Quick Commands)

Text Extraction (文本提取)

python

import pdfplumber
with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)

Table to Excel (表格转 Excel)

python

import pdfplumber
import pandas as pd
all_tables = []
with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            if table:
                df = pd.DataFrame(table[1:], columns=table[0])
                all_tables.append(df)
combined = pd.concat(all_tables, ignore_index=True)
combined.to_excel("extracted_tables.xlsx", index=False)

Merge PDFs (合并 PDF)

python

from pypdf import PdfWriter, PdfReader
writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
    reader = PdfReader(pdf_file)
    for page in reader.pages:
        writer.add_page(page)
with open("merged.pdf", "wb") as output:
    writer.write(output)

Split PDF (拆分 PDF)

python

from pypdf import PdfReader, PdfWriter
reader = PdfReader("large_document.pdf")
for i, page in enumerate(reader.pages):
    writer = PdfWriter()
    writer.add_page(page)
    with open(f"page_{i+1}.pdf", "wb") as output:
        writer.write(output)

Create PDF (创建 PDF)

python

from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
c = canvas.Canvas("hello.pdf", pagesize=letter)
width, height = letter
c.drawString(100, height - 100, "Hello World!")
c.save()

Extract Metadata (提取元信息)

python

from pypdf import PdfReader
reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Pages: {len(reader.pages)}")

依赖安装 (Dependencies Installation)

Python Dependencies

bash

pip install -r requirements.txt
# Includes: pypdf, pdfplumber, reportlab, pandas, openpyxl

常见场景示例 (Common Scenarios)

Scenario 1: Batch Extract Invoice Tables (批量提取发票表格)

python

import pdfplumber
import pandas as pd
import glob
all_data = []
for pdf_file in glob.glob("invoices/*.pdf"):
    with pdfplumber.open(pdf_file) as pdf:
        for page in pdf.pages:
            tables = page.extract_tables()
            for table in tables:
                if table:
                    df = pd.DataFrame(table[1:], columns=table[0])
                    df['source_file'] = pdf_file
                    all_data.append(df)
combined = pd.concat(all_data, ignore_index=True)
combined.to_excel("all_invoices.xlsx", index=False)

Scenario 2: Create Report with Table (生成带表格的报告)

python

from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph
from reportlab.lib.styles import getSampleStyleSheet
doc = SimpleDocTemplate("report.pdf", pagesize=letter)
styles = getSampleStyleSheet()
story = []
# Title
story.append(Paragraph("Sales Report", styles['Title']))
# Table
data = [
    ['Product', 'Q1', 'Q2', 'Q3', 'Q4'],
    ['Product A', '1000', '1200', '1100', '1300'],
    ['Product B', '800', '900', '950', '1000']
]
t = Table(data)
t.setStyle(TableStyle([
    ('BACKGROUND', (0, 0), (-1, 0), 'grey'),
    ('TEXTCOLOR', (0, 0), (-1, 0), 'white'),
    ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
    ('GRID', (0, 0), (-1, -1), 1, 'black')
]))
story.append(t)
doc.build(story)

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