بنقرة واحدة
pdf-offline
PDF 文档离线读写与表单处理:提取文本/表格、合并拆分、生成 PDF、填写表单。适用于“本地处理/读取/生成 PDF 文件”(依赖安装可能需要网络)。
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
PDF 文档离线读写与表单处理:提取文本/表格、合并拆分、生成 PDF、填写表单。适用于“本地处理/读取/生成 PDF 文件”(依赖安装可能需要网络)。
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
指导编码智能体以 capability-runtime 为业务落地入口,交付基于 capability-runtime 的 skills / agents / workflows,并在 Greenfield 或 Legacy Convergence 场景下优先使用 Runtime public surface、structured output、NodeReport、host summary 与 service/session surfaces。只要任务目标是用 capability-runtime / capability_runtime 落地业务代码、收敛下游 runtime boundary,或涉及 Runtime.run / Runtime.run_stream / run_structured / run_structured_stream / AgentSpec / PromptRenderMode / prompt_render_mode / _runtime_prompt / precomposed_messages / multimodal / vision / image input / 多图输入 / 视频抽帧输入 / OpenAI-compatible messages / image_url content parts / WorkflowSpec / NodeReport / RuntimeServiceFacade / describe_capability / summarize_host_run,就应优先使用本技能。不要用于普通通用编码、prompt-only 任务、直接学习上游原生框架 API,或任何明确要求“直接用 skills-runtime-sdk / Agently / provider SDK,不走 capability-runtime”的任务;若已触发但随后识别出这是反目标,必须立即退出,并停止提供任何上游实现细节、伪代码或 API 猜测。
Turn vague ideas into a validated design/spec through structured brainstorming. Use before any creative work - new features, UI/components, behavior changes, refactors, architecture decisions. Trigger whenever a user asks to brainstorm, define requirements, propose approaches, write a design doc, or says something like 'I want to build X' or 'how should we approach Y'. Even seemingly simple tasks benefit from a quick design pass.
用 Skills Runtime SDK(Python)开发复杂业务 agent、skills、workflow 的编码智能体指南。用户一旦提到 skills_runtime、Skills Runtime SDK、overlay YAML、FakeChatBackend、AgentBuilder、Coordinator、skill_ref_read、skill_exec、approvals/sandbox、WAL/replay、exec sessions、spawn_agent/send_input/wait、waiting_human/resume、examples/apps/workflows,或要在本仓上落地复杂业务开发/修复/回归,就应优先使用本技能。不要用于与本框架无关的通用编码或纯文案任务。
Trace and document the complete call chain / data flow of any feature or process in a codebase. Use this skill whenever the user asks to understand how a feature works end-to-end, trace a call chain, analyze code flow, map data flow across layers, reverse-engineer a process, or asks questions like "how does X call Y", "what happens when the user clicks Z", "trace the request from frontend to database". Also use it when the user wants the analysis exported to a file for offline reading.
Use only when the user explicitly wants to build with the Agently framework (mentions Agently/agently/OpenAICompatible/TriggerFlow/ToolExtension/ChromaCollection, or says “用 Agently 做/用 agently 做”). Deliver runnable code plus regression tests validating schema/ensure_keys and streaming (delta/instant/streaming_parse), with optional tools (Search/Browse/MCP), TriggerFlow orchestration, KB (ChromaDB), and serviceization (SSE/WS/HTTP). Do not use for generic streaming/testing questions that are not about Agently, or for prompt-only writing without tests/structure.
用 tmux 稳定驱动交互式 CLI:启动 session、发送按键、等待输出就绪,并支持 worker 向 controller pane 回传结果(backchannel)。
| name | pdf-offline |
| version | 0.1.1 |
| description | PDF 文档离线读写与表单处理:提取文本/表格、合并拆分、生成 PDF、填写表单。适用于“本地处理/读取/生成 PDF 文件”(依赖安装可能需要网络)。 |
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.
Assume the skill directory itself is the working directory when running bundled files from this skill.
This skill bundles a simple CLI (doc_utils.py) copied from the older pdf skill, so you can do common PDF operations quickly.
# Read PDF → JSON
python3 ./doc_utils.py read path/to/file.pdf
# Merge PDFs
python3 ./doc_utils.py merge merged.pdf a.pdf b.pdf
Optional deps install helper (Python-only, no system packages):
bash ./install.sh
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()
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)
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)
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}")
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)
import pdfplumber
with pdfplumber.open("document.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
print(text)
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)
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)
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()
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)
IMPORTANT: Never use Unicode subscript/superscript characters directly in ReportLab output. Built-in fonts often miss those glyphs and render black boxes.
Use ReportLab markup in Paragraph objects instead:
from reportlab.platypus import Paragraph
from reportlab.lib.styles import getSampleStyleSheet
styles = getSampleStyleSheet()
chemical = Paragraph("H<sub>2</sub>O", styles["Normal"])
squared = Paragraph("x<super>2</super> + y<super>2</super>", styles["Normal"])
# 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
# 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
# Merge
pdftk file1.pdf file2.pdf cat output merged.pdf
# Split
pdftk input.pdf burst
# Rotate
pdftk input.pdf rotate 1east output rotated.pdf
# 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)
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)
# Using pdfimages (poppler-utils)
pdfimages -j input.pdf output_prefix
# This extracts all images as output_prefix-000.jpg, output_prefix-001.jpg, etc.
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)
| 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 |