pdf

Una herramienta para trabajar con archivos PDF, un formato de documento que conserva el diseño al compartirlo. Puede extraer texto, crear documentos y combinar varios archivos.

In plain words
What is it for?
Sirve para extraer texto de PDFs, generar nuevos documentos y fusionar varios PDFs en uno.
Why use it?
Reduce el trabajo manual de leer documentos, producir PDFs o unir archivos separados. La información disponible no detalla más funciones.

Skill for Claude CodeCodex

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/wytheglobal/learn-claude-code/pdf
Any agent
npx skills add wytheglobal/learn-claude-code --skill pdf
Clone the repo
git clone --depth 1 https://github.com/wytheglobal/learn-claude-code

Made for: Claude Code, Codex.

Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 717 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 $0.00032 $0.00717
Opus 5 $0.00016 $0.00358
Sonnet 5 $0.00006 $0.00143
Haiku 4.5 $0.00003 $0.00072

Measured 3d ago against content hash b143723126a9, 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 3d 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.

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.

skills/pdf/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Processing Skill

You now have expertise in PDF manipulation. Follow these workflows:

Reading PDFs

Option 1: Quick text extraction (preferred)

# Using pdftotext (poppler-utils)
pdftotext input.pdf -  # Output to stdout
pdftotext input.pdf output.txt  # Output to file

# If pdftotext not available, try:
python3 -c "
import fitz  # PyMuPDF
doc = fitz.open('input.pdf')
for page in doc:
    print(page.get_text())
"

Option 2: Page-by-page with metadata

import fitz  # pip install pymupdf

doc = fitz.open("input.pdf")
print(f"Pages: {len(doc)}")
print(f"Metadata: {doc.metadata}")

for i, page in enumerate(doc):
    text = page.get_text()
    print(f"--- Page {i+1} ---")
    print(text)

Creating PDFs

Option 1: From Markdown (recommended)

# Using pandoc
pandoc input.md -o output.pdf

# With custom styling
pandoc input.md -o output.pdf --pdf-engine=xelatex -V geometry:margin=1in

Option 2: Programmatically

from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("output.pdf", pagesize=letter)
c.drawString(100, 750, "Hello, PDF!")
c.save()

Option 3: From HTML

# Using wkhtmltopdf
wkhtmltopdf input.html output.pdf

# Or with Python
python3 -c "
import pdfkit
pdfkit.from_file('input.html', 'output.pdf')
"

Merging PDFs

import fitz

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

Splitting PDFs

import fitz

doc = fitz.open("input.pdf")
for i in range(len(doc)):
    single = fitz.open()
    single.insert_pdf(doc, from_page=i, to_page=i)
    single.save(f"page_{i+1}.pdf")

Key Libraries

Task Library Install
Read/Write/Merge PyMuPDF pip install pymupdf
Create from scratch ReportLab pip install reportlab
HTML to PDF pdfkit pip install pdfkit + wkhtmltopdf
Text extraction pdftotext brew install poppler / apt install poppler-utils

Read the full file on GitHub · 113 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. 3d ago First seen · 113 lines · 32 tokens per session scan A b143723126a9

Subscribe to this mod's changes

pdf is a skill published in the GitHub repository wytheglobal/learn-claude-code (23 stars, last pushed 4mo ago), licensed MIT. It adds 32 tokens to every session and 717 once invoked, about $0.0002 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.

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