PDF Processing

A toolkit for working with PDF files, including extracting text and tables, filling forms, and combining or splitting documents.

In plain words
What is it for?
Use it to read multi-page PDFs, extract tables, fill PDF forms, merge documents, or select particular pages.
Why use it?
It removes the need to handle PDF content manually when information must be reused or documents must be reorganized.

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/justdvp/claude-code-templates/pdf-processing
Any agent
npx skills add Justdvp/claude-code-templates --skill pdf-processing
Clone the repo
git clone --depth 1 https://github.com/Justdvp/claude-code-templates

Made for: Claude Code, Codex.

Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 770 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00036 $0.00770
Opus 5 $0.00018 $0.00385
Sonnet 5 $0.00007 $0.00154
Haiku 4.5 $0.00004 $0.00077

Measured 2d ago against content hash 1bbb21910cec, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

PDF Processing 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 2d 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

Copies of this mod

1 near-identical copy found in the catalogue:

cli-tool/components/skills/document-processing/pdf-processing/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Processing

Quick start

Use pdfplumber to extract text from PDFs:

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    text = pdf.pages[0].extract_text()
    print(text)

Extracting tables

Extract tables from PDFs with automatic detection:

import pdfplumber

with pdfplumber.open("report.pdf") as pdf:
    page = pdf.pages[0]
    tables = page.extract_tables()

    for table in tables:
        for row in table:
            print(row)

Extracting all pages

Process multi-page documents efficiently:

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    full_text = ""
    for page in pdf.pages:
        full_text += page.extract_text() + "\n\n"

    print(full_text)

Form filling

For PDF form filling, see FORMS.md for the complete guide including field analysis and validation.

Merging PDFs

Combine multiple PDF files:

from pypdf import PdfMerger

merger = PdfMerger()

for pdf in ["file1.pdf", "file2.pdf", "file3.pdf"]:
    merger.append(pdf)

merger.write("merged.pdf")
merger.close()

Splitting PDFs

Extract specific pages or ranges:

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

# Extract pages 2-5
for page_num in range(1, 5):
    writer.add_page(reader.pages[page_num])

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

Available packages

  • pdfplumber - Text and table extraction (recommended)
  • pypdf - PDF manipulation, merging, splitting
  • pdf2image - Convert PDFs to images (requires poppler)
  • pytesseract - OCR for scanned PDFs (requires tesseract)

Common patterns

Extract and save text:

import pdfplumber

with pdfplumber.open("input.pdf") as pdf:
    text = "\n\n".join(page.extract_text() for page in pdf.pages)

with open("output.txt", "w") as f:
    f.write(text)

Extract tables to CSV:

import pdfplumber
import csv

with pdfplumber.open("tables.pdf") as pdf:
    tables = pdf.pages[0].extract_tables()

    with open("output.csv", "w", newline="") as f:
        writer = csv.writer(f)
        for table in tables:
            writer.writerows(table)

Read the full file on GitHub · 150 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 150 lines · 36 tokens per session scan A 1bbb21910cec

Subscribe to this mod's changes

PDF Processing is a skill published in the GitHub repository Justdvp/claude-code-templates (7 stars, last pushed 2d ago), licensed MIT. It adds 36 tokens to every session and 770 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.

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