pdf

pdf is a skill for Claude Code, Codex from TencentCloud/Octop. It costs 95 tokens per session (2,369 once invoked), scanned A, a copy of pdf, MIT.

A guide for working with PDF files, including reading, extracting text or tables, combining, splitting, rotating, watermarking, creating, securing, and scanning them with OCR. OCR makes text in scanned pages searchable.

In plain words
What is it for?
Use it to inspect, transform, create, secure, fill, or extract content from PDF documents.
Why use it?
It provides the documented tools and procedures needed for common PDF tasks, including files whose text cannot be selected directly.

Skill for Claude CodeCodex

About the project

Octop is a self-hosted, multi-user AI assistant that runs multiple specialized agents and connects them to chat interfaces, tools, and external services. It is for individuals, families, and teams who want a locally operated assistant with shared experts and persistent capabilities. Catalogue add-ons extend its agent and assistant workflows.

TencentCloud/Octop · 1,413 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/tencentcloud/octop/pdf
Any agent
npx skills add TencentCloud/Octop --skill pdf
Clone the repo
git clone --depth 1 https://github.com/TencentCloud/Octop

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pdf

README.md
[![agentmods](https://agentmods.dev/badge/skills/tencentcloud/octop/pdf.svg)](https://agentmods.dev/skills/tencentcloud/octop/pdf)
Your own site
<a href="https://agentmods.dev/skills/tencentcloud/octop/pdf"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/pdf.svg" alt="Measured on agentmods" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,369 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00095 $0.02369
Opus 5 $0.00048 $0.01184
Sonnet 5 $0.00019 $0.00474
Haiku 4.5 $0.00010 $0.00237

Measured 5d ago against content hash d81e0d27245f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pdf scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/check_bounding_boxes.py, scripts/check_fillable_fields.py, scripts/convert_pdf_to_images.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to pdf — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

src/octop/infra/agents/experts/library/office-automation/skills/pdf/SKILL.md · 330 lines

How it starts

The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.

重要: 所有 scripts/ 路径均相对于此技能目录。 运行方式:cd {this_skill_dir} && python scripts/... 或使用 execute_shell_commandcwd 参数。

PDF 处理指南

前置要求

  • pypdf:核心 PDF 读写功能
  • pdfplumber:文本和表格提取
  • reportlab:PDF 创建
  • pdftotext (poppler-utils):命令行文本提取
  • pdftoppm (poppler-utils):PDF 转图片
  • qpdf:PDF 操作(合并、拆分、旋转、解密)

概述

本指南涵盖了使用 Python 库和命令行工具进行 PDF 处理的基本操作。有关高级功能、JavaScript 库和详细示例,请参阅 REFERENCE.md。如果需要填写 PDF 表单,请阅读 FORMS.md 并按照其中的说明操作。

快速入门

from pypdf import PdfReader, PdfWriter

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

# 提取文本
text = ""
for page in reader.pages:
    text += page.extract_text()

Python 库

pypdf - 基本操作

合并 PDF
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)
拆分 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)
提取元数据
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}")
旋转页面
reader = PdfReader("input.pdf")
writer = PdfWriter()

page = reader.pages[0]
page.rotate(90)  # 顺时针旋转 90 度
writer.add_page(page)

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

pdfplumber - 文本和表格提取

提取带布局的文本
import pdfplumber

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

Read the full file on GitHub · 330 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 330 lines · 95 tokens per session scan A d81e0d27245f

Subscribe to this mod's changes

pdf is a skill published in the GitHub repository TencentCloud/Octop (1,413 stars, last pushed yesterday), licensed MIT. It adds 95 tokens to every session and 2,369 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pdf, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

google-docs

Google Docs via gws: read, append text, structured batch edits.

Open-Curiosity/gini-agent · 19 tokens

google-sheets

Google Sheets via gws: read/write cells, append rows, structured batch edits.

Open-Curiosity/gini-agent · 21 tokens

pdf

当用户需要对PDF文件进行任何操作时,请使用此技能。包括从 PDF 中读取或提取文本/表格、合并多个 PDF、拆分 PDF、旋转页面、添加水印、创建新PDF、填写PDF表单、加密/解密 PDF、提取图片,以及对扫描版 PDF 进行 OCR 使其可搜索。如果用户提到 .pdf 文件或要求生成 PDF,请使用此技能。.

agentscope-ai/QwenPaw · 95 tokens

adk-unit-design

Writes an as-built architecture document for one ADK code unit — purpose, execution flow, data flow, cross-class dependencies, extension points, and the parts that must not change — to docs/design/{topic}/{unit}/index.md. It describes the code as implemented, not a proposed design, and its reader is a developer about…

google/adk-python · 181 tokens

hive.pdf

Read, write, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python (pypdf, pdfplumber, reportlab, pypdfium2) and command-line tools (poppler-utils, qpdf). Use when the user asks to extract text/tables/images from a PDF, create or modify a PDF, combine or split PDFs, OCR a scanned PDF…

aden-hive/hive · 98 tokens

pdf-toolkit

Structured .pdf operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract…

opensquilla/opensquilla · 127 tokens