* 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>
13 KiB
name, description, version, type, risk_level, status, disable-model-invocation, tags, metadata, market
| name | description | version | type | risk_level | status | disable-model-invocation | tags | metadata | market | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill. Use when 用户提到 PDF、读取PDF、合并PDF、拆分PDF、填写表单、加水印、提取文字、 扫描识别。 | 1.0.2 | procedural | low | enabled | true |
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pdf skill
L0: One-Sentence Summary
Read, create, merge, split, and fill PDF documents, with OCR support and command-line tools.
L1: Overview and Use Cases
Capability Description
pdf is a Procedural Skill that provides full PDF document processing capabilities. Built on Python libraries (pypdf, pdfplumber, reportlab) and command-line tools (qpdf, pdftotext, pdftk), it supports text extraction, table extraction, merging/splitting, rotation, watermarking, encryption, form filling, and OCR.
Use Cases
- The user needs to extract text or table data from a PDF
- The user needs to merge multiple PDFs or split pages
- The user needs to create a new PDF document
- The user needs to fill PDF forms, add watermarks, or encrypt PDFs
L2: Detailed Specification
Prerequisites
Python 3 (required)
Before performing any Python operation, check that Python is available:
python3 --version 2>/dev/null || python --version 2>/dev/null
If the command fails (Python is not available), you must stop and tell the user to install Python 3:
- macOS:
brew install python3, or download from https://www.python.org/downloads/ - Windows:
winget install Python.Python.3, or download from python.org (check "Add Python to PATH" during installation) - Linux (Debian/Ubuntu):
sudo apt install python3 python3-pip - Linux (Fedora/RHEL):
sudo dnf install python3 python3-pip
For more detailed environment setup help: load the python-runtime skill for Python issues;
load the dev-environment-setup skill for everything else (system tools like poppler / tesseract, containers / WSL).
Python Package Dependencies
This skill depends on the following Python packages (checked on demand):
pypdf— Basic PDF operations (read, merge, split, rotate)pdfplumber— Table extraction, layout-aware text extractionPillow— Image processing (watermarks, verification images, etc.)reportlab— PDF creation (optional, install on demand)pdf2image— PDF-to-image conversion (optional, requires poppler)
Core package check:
python3 -c "import pypdf; import pdfplumber; import PIL" 2>/dev/null || echo "MISSING"
If missing, tell the user to install: 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: "File saved to: /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