pdf-toolkit

pdf-toolkit is a skill for Claude Code, Codex from malue-ai/dazee-small. It costs 33 tokens per session (823 once invoked), scanned A, original, MIT.

A toolkit for working with PDF files, including combining, splitting, protecting, watermarking, reading text, and converting PDFs to Word documents.

In plain words
What is it for?
Use it to merge or extract pages, add passwords or text watermarks, pull out text, and convert PDF documents.
Why use it?
It handles common document changes in one workflow instead of requiring separate manual tools for each operation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to merge or extract pages, add passwords or text watermarks, pull out text, and convert PDF documents.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/malue-ai/dazee-small/pdf-toolkit
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.

Any agent
npx skills add malue-ai/dazee-small --skill pdf-toolkit
Clone the repo
git clone --depth 1 https://github.com/malue-ai/dazee-small

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-toolkit

README.md
[![agentmods](https://agentmods.dev/badge/skills/malue-ai/dazee-small/pdf-toolkit.svg)](https://agentmods.dev/skills/malue-ai/dazee-small/pdf-toolkit)
Your own site
<a href="https://agentmods.dev/skills/malue-ai/dazee-small/pdf-toolkit"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/pdf-toolkit.svg" alt="Measured on agentmods" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 823 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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 5.1 $0.00033 $0.00823
Opus 5 $0.00016 $0.00411
Sonnet 5 $0.00007 $0.00165
Haiku 4.5 $0.00003 $0.00082

Measured 8d ago against content hash 35051496b46a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pdf-toolkit 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 8d ago.

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.

instances/xiaodazi/skills/pdf-toolkit/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF 工具箱

帮助用户完成各种 PDF 操作:合并、拆分、加密、加水印、提取文本、转换格式。

使用场景

  • 用户说「把这 5 个 PDF 合并成一个」「拆分这个 PDF 的第 3-10 页」
  • 用户说「给 PDF 加个密码」「加个水印」
  • 用户说「提取 PDF 里的文字」「PDF 转 Word」

依赖安装

首次使用时自动安装:

pip install pypdf reportlab

执行方式

通过 Python 脚本使用 pypdf 和 reportlab 处理 PDF。

合并 PDF

from pypdf import PdfWriter

writer = PdfWriter()
for pdf_path in ["/path/to/1.pdf", "/path/to/2.pdf", "/path/to/3.pdf"]:
    writer.append(pdf_path)

writer.write("/path/to/merged.pdf")
writer.close()
print("合并完成")

拆分 PDF

from pypdf import PdfReader, PdfWriter

reader = PdfReader("/path/to/input.pdf")
writer = PdfWriter()

# 提取第 3-10 页(0-indexed)
for page_num in range(2, 10):
    writer.add_page(reader.pages[page_num])

writer.write("/path/to/extracted.pdf")
writer.close()

加密 PDF

from pypdf import PdfReader, PdfWriter

reader = PdfReader("/path/to/input.pdf")
writer = PdfWriter()

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

writer.encrypt("user_password")
writer.write("/path/to/encrypted.pdf")
writer.close()

添加文字水印

from pypdf import PdfReader, PdfWriter
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import A4
import io

# 创建水印 PDF
packet = io.BytesIO()
c = canvas.Canvas(packet, pagesize=A4)
c.setFont("Helvetica", 40)
c.setFillAlpha(0.3)
c.saveState()
c.translate(300, 400)
c.rotate(45)
c.drawCentredString(0, 0, "CONFIDENTIAL")
c.restoreState()
c.save()
packet.seek(0)

# 叠加水印
watermark = PdfReader(packet)
reader = PdfReader("/path/to/input.pdf")
writer = PdfWriter()

for page in reader.pages:
    page.merge_page(watermark.pages[0])
    writer.add_page(page)

writer.write("/path/to/watermarked.pdf")

提取文本

from pypdf import PdfReader

reader = PdfReader("/path/to/input.pdf")
text = ""
for page in reader.pages:
    text += page.extract_text() + "\n"

print(f"共 {len(reader.pages)} 页,提取文本 {len(text)} 字符")

安全规则

  • 加密操作确认密码:提醒用户牢记密码,PDF 加密后无法恢复
  • 合并前确认顺序:列出文件顺序让用户确认
  • 不覆盖原文件:输出到新文件,保留原始 PDF

Read the full file on GitHub · 140 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. 8d ago First seen · 140 lines · 33 tokens per session scan A 35051496b46a

Subscribe to this mod's changes

pdf-toolkit is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 823 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.