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David-Li0406/meta-skill-evloving

Kit de ferramentas abrangente para manipulação de PDFs: extração de texto e tabelas, criação de novos PDFs, mesclagem/divisão de documentos e manipulação de formulários.

O que é meta-skill-evloving?

Este skill fornece um conjunto completo de ferramentas e exemplos práticos para processamento de PDFs em Python e linha de comando. Ele cobre desde operações básicas como leitura, extração de texto e metadados com a biblioteca pypdf, até extração avançada de tabelas com pdfplumber e criação de PDFs com reportlab. Inclui também ferramentas de linha de comando como pdftotext, qpdf e pdftk para tarefas rápidas. O guia é útil para desenvolvedores que precisam automatizar a manipulação de PDFs em escala, abordando tarefas comuns como mesclagem, divisão, rotação, adição de marcas d'água, OCR em PDFs escaneados e proteção por senha. Uma tabela de referência rápida ajuda a escolher a melhor ferramenta para cada tarefa, e seções de próximos passos direcionam para documentação adicional sobre preenchimento de formulários e bibliotecas JavaScript.

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Documentação

Guia de Processamento de PDF

Visão Geral

Este guia cobre operações essenciais de processamento de PDF usando bibliotecas Python e ferramentas de linha de comando. Para recursos avançados, bibliotecas JavaScript e exemplos detalhados, consulte o arquivo reference.md. Se você precisar preencher um formulário PDF, leia forms.md e siga suas instruções.

Início Rápido

from pypdf import PdfReader, PdfWriter

# Ler um PDF
reader = PdfReader("document.pdf")
print(f"Páginas: {len(reader.pages)}")

# Extrair texto
text = ""
for page in reader.pages:
    text += page.extract_text()

Bibliotecas Python

pypdf - Operações Básicas

Mesclar PDFs

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)

Dividir PDF

reader = PdfReader("input.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)

Extrair Metadados

reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Título: {meta.title}")
print(f"Autor: {meta.author}")
print(f"Assunto: {meta.subject}")
print(f"Criador: {meta.creator}")

Girar Páginas

reader = PdfReader("input.pdf")
writer = PdfWriter()

page = reader.pages[0]
page.rotate(90)  # Girar 90 graus no sentido horário
writer.add_page(page)

with open("rotated.pdf", "wb") as output:
    writer.write(output)

pdfplumber - Extração de Texto e Tabelas

Extrair Texto com Layout

import pdfplumber

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

Extrair Tabelas

with pdfplumber.open("document.pdf") as pdf:
    for i, page in enumerate(pdf.pages):
        tables = page.extract_tables()
        for j, table in enumerate(tables):
            print(f"Tabela {j+1} na página {i+1}:")
            for row in table:
                print(row)

Extração Avançada de Tabelas

import pandas as pd

with pdfplumber.open("document.pdf") as pdf:
    all_tables = []
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            if table:  # Verificar se a tabela não está vazia
                df = pd.DataFrame(table[1:], columns=table[0])
                all_tables.append(df)

# Combinar todas as tabelas
if all_tables:
    combined_df = pd.concat(all_tables, ignore_index=True)
    combined_df.to_excel("extracted_tables.xlsx", index=False)

reportlab - Criar PDFs

Criação Básica de PDF

from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("hello.pdf", pagesize=letter)
width, height = letter

# Adicionar texto
c.drawString(100, height - 100, "Olá Mundo!")
c.drawString(100, height - 120, "Este é um PDF criado com reportlab")

# Adicionar uma linha
c.line(100, height - 140, 400, height - 140)

# Salvar
c.save()

Criar PDF com Múltiplas Páginas

from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
from reportlab.lib.styles import getSampleStyleSheet

doc = SimpleDocTemplate("report.pdf", pagesize=letter)
styles = getSampleStyleSheet()
story = []

# Adicionar conteúdo
title = Paragraph("Título do Relatório", styles['Title'])
story.append(title)
story.append(Spacer(1, 12))

body = Paragraph("Este é o corpo do relatório. " * 20, styles['Normal'])
story.append(body)
story.append(PageBreak())

# Página 2
story.append(Paragraph("Página 2", styles['Heading1']))
story.append(Paragraph("Conteúdo para a página 2", styles['Normal']))

# Construir PDF
doc.build(story)

Ferramentas de Linha de Comando

pdftotext (poppler-utils)

# Extrair texto
pdftotext input.pdf output.txt

# Extrair texto preservando layout
pdftotext -layout input.pdf output.txt

# Extrair páginas específicas
pdftotext -f 1 -l 5 input.pdf output.txt  # Páginas 1-5

qpdf

# Mesclar PDFs
qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf

# Dividir páginas
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf
qpdf input.pdf --pages . 6-10 -- pages6-10.pdf

# Girar páginas
qpdf input.pdf output.pdf --rotate=+90:1  # Girar página 1 em 90 graus

# Remover senha
qpdf --password=minhasenha --decrypt encrypted.pdf decrypted.pdf

pdftk (se disponível)

# Mesclar
pdftk file1.pdf file2.pdf cat output merged.pdf

# Dividir
pdftk input.pdf burst

# Girar
pdftk input.pdf rotate 1east output rotated.pdf

Tarefas Comuns

Extrair Texto de PDFs Escaneados

# Requer: pip install pytesseract pdf2image
import pytesseract
from pdf2image import convert_from_path

# Converter PDF em imagens
images = convert_from_path('scanned.pdf')

# OCR em cada página
text = ""
for i, image in enumerate(images):
    text += f"Página {i+1}:\n"
    text += pytesseract.image_to_string(image)
    text += "\n\n"

print(text)

Adicionar Marca d'Água

from pypdf import PdfReader, PdfWriter

# Criar marca d'água (ou carregar existente)
watermark = PdfReader("watermark.pdf").pages[0]

# Aplicar a todas as páginas
reader = PdfReader("document.pdf")
writer = PdfWriter()

for page in reader.pages:
    page.merge_page(watermark)
    writer.add_page(page)

with open("watermarked.pdf", "wb") as output:
    writer.write(output)

Extrair Imagens

# Usando pdfimages (poppler-utils)
pdfimages -j input.pdf output_prefix

# Extrai todas as imagens como output_prefix-000.jpg, output_prefix-001.jpg, etc.

Proteção por Senha

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

for page in reader.pages:
    writer.add_page(page)

# Adicionar senha
writer.encrypt("senhausuario", "senhadono")

with open("encrypted.pdf", "wb") as output:
    writer.write(output)

Referência Rápida

TarefaMelhor FerramentaComando/Código
Mesclar PDFspypdfwriter.add_page(page)
Dividir PDFspypdfUma página por arquivo
Extrair textopdfplumberpage.extract_text()
Extrair tabelaspdfplumberpage.extract_tables()
Criar PDFsreportlabCanvas ou Platypus
Mesclar por linha de comandoqpdfqpdf --empty --pages ...
OCR em PDFs escaneadospytesseractConverter para imagem primeiro
Preencher formulários PDFpdf-lib ou pypdf (veja forms.md)Veja forms.md

Próximos Passos

  • Para uso avançado do pypdfium2, consulte reference.md
  • Para bibliotecas JavaScript (pdf-lib), consulte reference.md
  • Se precisar preencher um formulário PDF, siga as instruções em forms.md
  • Para guias de solução de problemas, consulte reference.md

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

David-Li0406/meta-skill-evloving

Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website", "log into", or any browser interaction request.

David-Li0406/meta-skill-evloving

Create technical diagrams using Mermaid syntax for architecture, sequences, ERDs, flowcharts, and state machines. Use for visualizing system design, data flows, and processes. Triggers: diagram, mermaid, architecture diagram, sequence diagram, flowchart, ERD, entity relationship, state diagram, C4 model, component diagram, visualize, draw.

David-Li0406/meta-skill-evloving

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

David-Li0406/meta-skill-evloving

Complete color manipulation and green screen effects system. PROACTIVELY activate for: (1) Green screen/chromakey removal, (2) Color grading with LUTs, (3) Color correction (levels, curves, white balance), (4) Colorkey/color removal effects, (5) Hue/saturation manipulation, (6) Color space conversions (BT.709, BT.2020, HDR), (7) Color isolation effects, (8) Teal and orange look, (9) Vintage/film looks, (10) Color keying for transparency. Provides: chromakey and colorkey filters, LUT application (lut3d), curves and levels adjustment, color balance, selective color manipulation, color space handling, HDR tone mapping, professional color grading chains.

David-Li0406/meta-skill-evloving

Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.

David-Li0406/meta-skill-evloving

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

David-Li0406/meta-skill-evloving

Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.

David-Li0406/meta-skill-evloving

Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks

David-Li0406/meta-skill-evloving

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

David-Li0406/meta-skill-evloving

Download YouTube videos with customizable quality and format options. Use this skill when the user asks to download, save, or grab YouTube videos. Supports various quality settings (best, 1080p, 720p, 480p, 360p), multiple formats (mp4, webm, mkv), and audio-only downloads as MP3.

David-Li0406/meta-skill-evloving

Best practices for Remotion - Video creation in React

David-Li0406/meta-skill-evloving

Provides bidirectional translation (Chinese/English), grammar checking, and sentence polishing. Supports specific tense constraints, context-aware tone adjustment, and natural expression optimization. Outputs direct text without formatting.

David-Li0406/meta-skill-evloving

指导如何通过自定义注解(如@Unicom)标识Dubbo接口,利用BeanDefinitionRegistryPostProcessor在启动时扫描并动态注册ReferenceBean,实现RPC调用的封装。

David-Li0406/meta-skill-evloving

生成Python脚本,利用FFmpeg将图片序列按3x3布局合并,或将合并图拆分。要求使用subprocess模块执行命令,并支持用户交互式输入路径。

David-Li0406/meta-skill-evloving

SOP for extracting and analyzing promotional activity details, handling time formatting, location mapping, payment logic, and step-by-step process validation.

David-Li0406/meta-skill-evloving

Specializes in creating TikTok short video scripts using an anthropomorphic 'Chef' perspective to explain wildlife food chains and survival environments, utilizing real field footage.

David-Li0406/meta-skill-evloving

针对TikTok平台,以拟人化视角(如动物作为厨师)创作系列短视频脚本。重点介绍野生动物、食物链及生态环境,要求使用野外实拍素材,风格幽默且具有教育意义。

David-Li0406/meta-skill-evloving

Generates KWL (Know, Want to know, Learned) charts for educational videos, specifically BrainPOP, using simple 7th-grade language and short, concise bullet points.

David-Li0406/meta-skill-evloving

Develops DAX measures to calculate promo and regular volumes and generates a calculated table of dates excluding continuous promo date ranges, handling multiple periods and nulls.

David-Li0406/meta-skill-evloving

Tracks complex, multi-session work using the Beads issue tracker and dependency graphs, and provides persistent memory that survives conversation compaction. Use when work spans multiple sessions, has complex dependencies, or needs persistent context across compaction cycles. Trigger with phrases like "create task for", "what's ready to work on", "show task", "track this work", "what's blocking", or "update status".

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