Files
market/skills/pdf/SKILL.zh-CN.md
Yige 1f7c8b9673 feat: skills i18n 改造(schemaVersion 1.1,零向后兼容) (#1)
* feat: skills i18n 改造 — schemaVersion 1.1,零向后兼容

把 21 个 skills + 1 个 agent + manifest/categories 全量迁移到 schemaVersion 1.1
的 i18n 结构,配套 CI AI 翻译流水线(GitHub Models)与本地工具链。

## 关键变更

### 数据结构(破坏性,schemaVersion 1.0 → 1.1)
- SKILL.md: 顶层 name 改为 ASCII slug(== 目录名,符合 agentskills.io 规范);
  中文显示名/short_desc/description 全部迁入 metadata.i18n.<locale>
- agents/<id>/agent.json: shortDesc/fullDesc/tags/persona.{role,traits} 迁入
  i18n.<locale>;changelog[].changes 改为 { <locale>: string[] } 对象
- categories.json: 每个分类的 label/description 迁入 i18n.<locale>,顶层只剩
  color/icon
- manifest.json: 加 supportedLocales / defaultLocale;顶层 description 迁入
  i18n.<locale>

### Body 文件结构
- 根 SKILL.md = frontmatter + default_locale (en-US) body
- SKILL.<locale>.md = 各 locale 的 markdown body(首行 <!-- locale: xx --> 自校验)

### 工具链(scripts/i18n/)
- glossary.json: zh→en 术语表 + do_not_translate 白名单
- schema/skill-frontmatter.schema.json: i18n frontmatter JSON Schema
- validate-i18n.py: 8 条校验规则(name 合规 / locale 完整性 / hash 一致性等)
- translate.py: GitHub Models / Anthropic 双 backend,sha256 增量翻译
- migrate.py: 一次性迁移脚本(旧格式 → i18n 结构)

### CI(.github/workflows/)
- i18n-validate.yml: PR 触发跑 validate + translate --check
- i18n-translate.yml: PR 触发用 GitHub Models(默认 openai/gpt-5-mini)翻译缺失
  locale,自动追加 commit;可切到 ANTHROPIC_API_KEY 走 Claude

### 文档
- docs/I18N.md: 作者贡献指南(schema 说明 / 提交流程 / 常见问题)
- README.md: 加多语言段落

## 验证

- uv run scripts/i18n/validate-i18n.py: OK,49 文件 0 错误
- uv run scripts/i18n/translate.py --check: 0 stale locale
- 21 skills 标题数 zh-CN == en-US 严格对齐(最大 66=66)
- skills-ref 规范校验:全部通过(顶层 name ASCII slug + description 单字段)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(i18n): 修复 PR #1 review 反馈的 6 项问题

- schema: translated_by 正则放宽为 ^(human|ai:[A-Za-z0-9._:/-]+)$,接受
  'ai:github:openai/gpt-5-mini' 这类 backend:model 形式(CI 翻译输出格式)
- README + docs/I18N.md: 修正"CI 用 Claude API"误导描述,正确说明默认是
  GitHub Models(openai/gpt-5-mini)+ GITHUB_TOKEN,可选切到 Anthropic
- skills/minimax-tts/SKILL.md & SKILL.zh-CN.md: 删除多余的 ``` 闭合,避免
  Markdown 后续渲染错乱
- skills/docx/SKILL.md: 翻译时丢失的 • Unicode escape 示例已恢复,
  与 zh-CN 版本对齐

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-05 00:26:33 +08:00

9.6 KiB
Raw Blame History

pdf 技能

L0一句话摘要

读取、创建、合并、拆分和填写 PDF 文档,支持 OCR 识别和命令行工具。

L1概述与使用场景

能力描述

pdf 是一个流程型技能Procedural Skill,提供 PDF 文档的完整处理能力。基于 Python 库pypdf、pdfplumber、reportlab和命令行工具qpdf、pdftotext、pdftk支持文本提取、表格提取、合并拆分、旋转、水印、加密、表单填写和 OCR 识别。

使用场景

  • 用户需要从 PDF 中提取文本或表格数据
  • 用户需要合并多个 PDF 或拆分页面
  • 用户需要创建新的 PDF 文档
  • 用户需要填写 PDF 表单、添加水印或加密

L2详细规范

Prerequisites

Python 3必需

在执行任何 Python 操作之前,先检测 Python 是否可用:

python3 --version 2>/dev/null || python --version 2>/dev/null

如果命令失败Python 不可用),必须停止并告知用户安装 Python 3

  • macOS: brew install python3 或从 https://www.python.org/downloads/ 下载
  • Windows: winget install Python.Python.3 或从 python.org 下载(安装时勾选 "Add Python to PATH"
  • Linux (Debian/Ubuntu): sudo apt install python3 python3-pip
  • Linux (Fedora/RHEL): sudo dnf install python3 python3-pip

如需更详细的环境配置帮助Python 相关问题加载 python-runtime 技能; 其他(系统工具如 poppler / tesseract、容器 / WSL加载 dev-environment-setup 技能。

Python 包依赖

本技能依赖以下 Python 包(按需检测):

  • pypdf — PDF 基础操作(读取、合并、拆分、旋转)
  • pdfplumber — 表格提取、带布局的文本提取
  • Pillow — 图片处理(水印、验证图等)
  • reportlab — PDF 创建(可选,按需安装)
  • pdf2image — PDF 转图片(可选,需要 poppler

核心包检测:

python3 -c "import pypdf; import pdfplumber; import PIL" 2>/dev/null || echo "MISSING"

缺失时告知用户安装:pip install pypdf pdfplumber Pillow

Output Rule

When you create or modify a .pdf file, you MUST tell the user the absolute path of the output file in your response. Example: "文件已保存到:/path/to/output.pdf"

Overview

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see REFERENCE.md. If you need to fill out a PDF form, read FORMS.md and follow its instructions.

Quick Start

from pypdf import PdfReader, PdfWriter

# Read a PDF
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")

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

Python Libraries

pypdf - Basic Operations

Merge 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)

Split 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)

Extract Metadata

reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Subject: {meta.subject}")
print(f"Creator: {meta.creator}")

Rotate Pages

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

page = reader.pages[0]
page.rotate(90)  # Rotate 90 degrees clockwise
writer.add_page(page)

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

pdfplumber - Text and Table Extraction

Extract Text with Layout

import pdfplumber

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

Extract Tables

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"Table {j+1} on page {i+1}:")
            for row in table:
                print(row)

Advanced Table Extraction

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:  # Check if table is not empty
                df = pd.DataFrame(table[1:], columns=table[0])
                all_tables.append(df)

# Combine all tables
if all_tables:
    combined_df = pd.concat(all_tables, ignore_index=True)
    combined_df.to_excel("extracted_tables.xlsx", index=False)

reportlab - Create PDFs

Basic PDF Creation

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

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

# Add text
c.drawString(100, height - 100, "Hello World!")
c.drawString(100, height - 120, "This is a PDF created with reportlab")

# Add a line
c.line(100, height - 140, 400, height - 140)

# Save
c.save()

Create PDF with Multiple Pages

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 = []

# Add content
title = Paragraph("Report Title", styles['Title'])
story.append(title)
story.append(Spacer(1, 12))

body = Paragraph("This is the body of the report. " * 20, styles['Normal'])
story.append(body)
story.append(PageBreak())

# Page 2
story.append(Paragraph("Page 2", styles['Heading1']))
story.append(Paragraph("Content for page 2", styles['Normal']))

# Build PDF
doc.build(story)

Subscripts and Superscripts

IMPORTANT: Never use Unicode subscript/superscript characters (₀₁₂₃₄₅₆₇₈₉, ⁰¹²³⁴⁵⁶⁷⁸⁹) in ReportLab PDFs. The built-in fonts do not include these glyphs, causing them to render as solid black boxes.

Instead, use ReportLab's XML markup tags in Paragraph objects:

from reportlab.platypus import Paragraph
from reportlab.lib.styles import getSampleStyleSheet

styles = getSampleStyleSheet()

# Subscripts: use <sub> tag
chemical = Paragraph("H<sub>2</sub>O", styles['Normal'])

# Superscripts: use <super> tag
squared = Paragraph("x<super>2</super> + y<super>2</super>", styles['Normal'])

For canvas-drawn text (not Paragraph objects), manually adjust font the size and position rather than using Unicode subscripts/superscripts.

Command-Line Tools

pdftotext (poppler-utils)

# Extract text
pdftotext input.pdf output.txt

# Extract text preserving layout
pdftotext -layout input.pdf output.txt

# Extract specific pages
pdftotext -f 1 -l 5 input.pdf output.txt  # Pages 1-5

qpdf

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

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

# Rotate pages
qpdf input.pdf output.pdf --rotate=+90:1  # Rotate page 1 by 90 degrees

# Remove password
qpdf --password=mypassword --decrypt encrypted.pdf decrypted.pdf

pdftk (if available)

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

# Split
pdftk input.pdf burst

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

Common Tasks

Extract Text from Scanned PDFs

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

# Convert PDF to images
images = convert_from_path('scanned.pdf')

# OCR each page
text = ""
for i, image in enumerate(images):
    text += f"Page {i+1}:\n"
    text += pytesseract.image_to_string(image)
    text += "\n\n"

print(text)

Add Watermark

from pypdf import PdfReader, PdfWriter

# Create watermark (or load existing)
watermark = PdfReader("watermark.pdf").pages[0]

# Apply to all pages
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)

Extract Images

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

# This extracts all images as output_prefix-000.jpg, output_prefix-001.jpg, etc.

Password Protection

from pypdf import PdfReader, PdfWriter

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

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

# Add password
writer.encrypt("userpassword", "ownerpassword")

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

Quick Reference

Task Best Tool Command/Code
Merge PDFs pypdf writer.add_page(page)
Split PDFs pypdf One page per file
Extract text pdfplumber page.extract_text()
Extract tables pdfplumber page.extract_tables()
Create PDFs reportlab Canvas or Platypus
Command line merge qpdf qpdf --empty --pages ...
OCR scanned PDFs pytesseract Convert to image first
Fill PDF forms pdf-lib or pypdf (see FORMS.md) See FORMS.md

Next Steps

  • For advanced pypdfium2 usage, see REFERENCE.md
  • For JavaScript libraries (pdf-lib), see REFERENCE.md
  • If you need to fill out a PDF form, follow the instructions in FORMS.md
  • For troubleshooting guides, see REFERENCE.md