pdf-processing

pdf-processing is a skill for Claude Code, Codex from beita6969/ScienceClaw. It costs 36 tokens per session (770 once invoked), scanned A, original, MIT.

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

In plain words
What is it for?
It helps extract text and tables, fill PDF forms, merge documents, and split selected pages using code.
Why use it?
It removes repetitive manual work when information is stored in PDFs rather than editable files.

Skill for Claude CodeCodex

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

Good fit It helps extract text and tables, fill PDF forms, merge documents, and…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/beita6969/scienceclaw/pdf-processing
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 beita6969/ScienceClaw --skill pdf-processing
Clone the repo
git clone --depth 1 https://github.com/beita6969/ScienceClaw

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-processing

README.md
[![agentmods](https://agentmods.dev/badge/skills/beita6969/scienceclaw/pdf-processing.svg)](https://agentmods.dev/skills/beita6969/scienceclaw/pdf-processing)
Your own site
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/pdf-processing"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/pdf-processing.svg" alt="Measured on agentmods" height="20"></a>
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. 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 $0.00036 $0.00770
Opus 5 $0.00018 $0.00385
Sonnet 5 $0.00007 $0.00154
Haiku 4.5 $0.00004 $0.00077

Measured 3d ago against content hash d3715a8e0c75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, 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 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

Copies of this mod

2 near-identical copies found in the catalogue:

skills/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. 3d ago First seen · 150 lines · 36 tokens per session scan A d3715a8e0c75

Subscribe to this mod's changes

pdf-processing is a skill published in the GitHub repository beita6969/ScienceClaw (894 stars, last pushed 3mo 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 2026-09-03.

Related

Other skills, from other repositories

pdf

PDF files: create, read, merge, fill, OCR, edit text.

NousResearch/hermes-agent · 18 tokens

pydicom

Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.

K-Dense-AI/scientific-agent-skills · 56 tokens

liteparse

Local document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities…

K-Dense-AI/scientific-agent-skills · 86 tokens

markitdown

Convert heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.

K-Dense-AI/scientific-agent-skills · 61 tokens

open-notebook

Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker…

K-Dense-AI/scientific-agent-skills · 123 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