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Pdf

Community
nuoyimanaituling
pdf

Process PDF files - extract text, read content, create PDFs, merge or split documents. Use when user asks to read, create, or manipulate PDF files.

Overview

Publishernuoyimanaituling
Repositorymanus-x
Skill namepdf
Stars
830
Forks
9
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nuoyimanaituling on GitHub. Read the source before you install it.

Installation

Install the Pdf AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nuoyimanaituling/manus-x/tree/master/backend/skills/pdf
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nuoyimanaituling/manus-x.git /tmp/manus-x
mkdir -p .claude/skills
cp -r /tmp/manus-x/backend/skills/pdf .claude/skills/pdf
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pdf in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pdf on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pdf is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PDF Processing Skill

You now have expertise in PDF file processing. Follow these instructions based on the task.

Reading PDFs

Using pdftotext (Recommended for text extraction)

bash
# Install if needed
apt-get install -y poppler-utils

# Extract text from PDF
pdftotext input.pdf output.txt

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

# Extract with layout preservation
pdftotext -layout input.pdf output.txt

Using Python PyMuPDF

python
import fitz  # PyMuPDF

# Open and read PDF
doc = fitz.open("input.pdf")
for page_num, page in enumerate(doc):
    text = page.get_text()
    print(f"--- Page {page_num + 1} ---")
    print(text)

# Extract text from specific pages
page = doc[0]  # First page (0-indexed)
text = page.get_text()

Using pdfplumber (for tables)

python
import pdfplumber

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

        # Extract tables
        tables = page.extract_tables()
        for table in tables:
            for row in table:
                print(row)

Creating PDFs

Using Python reportlab

python
from reportlab.lib.pagesizes import letter, A4
from reportlab.pdfgen import canvas
from reportlab.lib.units import inch

# Create a simple PDF
c = canvas.Canvas("output.pdf", pagesize=letter)
c.setFont("Helvetica", 12)
c.drawString(1*inch, 10*inch, "Hello World")
c.save()

Using Pandoc (from Markdown)

bash
# Install pandoc if needed
apt-get install -y pandoc texlive-xetex

# Convert Markdown to PDF
pandoc input.md -o output.pdf

# With custom template
pandoc input.md -o output.pdf --template=template.tex

Using weasyprint (from HTML)

python
from weasyprint import HTML

# From HTML string
html_content = "<h1>Hello World</h1><p>This is a PDF.</p>"
HTML(string=html_content).write_pdf("output.pdf")

# From HTML file
HTML("input.html").write_pdf("output.pdf")

Merging PDFs

python
import fitz

result = fitz.open()
for pdf_file in ["file1.pdf", "file2.pdf", "file3.pdf"]:
    doc = fitz.open(pdf_file)
    result.insert_pdf(doc)
result.save("merged.pdf")

Splitting PDFs

python
import fitz

doc = fitz.open("input.pdf")

# Extract specific pages
output = fitz.open()
output.insert_pdf(doc, from_page=0, to_page=4)  # Pages 1-5
output.save("pages_1_to_5.pdf")

# Split into individual pages
for i, page in enumerate(doc):
    single_page = fitz.open()
    single_page.insert_pdf(doc, from_page=i, to_page=i)
    single_page.save(f"page_{i+1}.pdf")

Adding Watermarks

python
import fitz

doc = fitz.open("input.pdf")
for page in doc:
    # Add text watermark
    page.insert_text(
        (100, 100),
        "CONFIDENTIAL",
        fontsize=50,
        color=(0.8, 0.8, 0.8),
        rotate=45
    )
doc.save("watermarked.pdf")

Key Libraries

LibraryUse CaseInstall
PyMuPDF (fitz)Read, write, merge, splitpip install pymupdf
pdftotextCLI text extractionapt install poppler-utils
pdfplumberTable extractionpip install pdfplumber
reportlabCreate PDFs programmaticallypip install reportlab
weasyprintHTML to PDFpip install weasyprint
pdf2imagePDF to imagespip install pdf2image
PyPDF2Merge, split, rotatepip install pypdf2

Best Practices

  1. Always check if required libraries are installed before use
  2. For large PDFs, process pages in batches to manage memory
  3. When extracting text, verify encoding (UTF-8 is recommended)
  4. For table extraction, pdfplumber is more reliable than PyMuPDF
  5. Close PDF documents after processing to free resources

Frequently asked questions

What does the Pdf AI skill do?

Process PDF files - extract text, read content, create PDFs, merge or split documents. Use when user asks to read, create, or manipulate PDF files.

Why use Pdf on TypingMind?

Because you install it once and use it with any model. Pdf is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pdf in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nuoyimanaituling/manus-x/tree/master/backend/skills/pdf. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pdf?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pdf?

As many as you like. As long as a model supports skills, you can use Pdf with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pdf AI skill free?

It is published on GitHub by nuoyimanaituling. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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