pdf

pdf is a skill for Claude Code, Codex from melandlabs/openloomi. It costs 92 tokens per session (2,109 once invoked), scanned A, a copy of pdf, Apache-2.0.

A guide for working with PDF files, which are fixed-layout documents. It covers reading text and metadata, extracting images or tables, merging and splitting files, rotating pages, filling forms, and applying protection.

In plain words
What is it for?
Use it to inspect, create, combine, separate, rotate, watermark, encrypt, decrypt, or fill PDF documents.
Why use it?
It provides standard ways to handle common PDF tasks without treating the document as an editable word-processing file.

Skill for Claude CodeCodex

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

Good fit Use it to inspect, create, combine, separate, rotate, watermark, encrypt, decrypt, or fill PDF documents.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/melandlabs/openloomi/pdf
About the project

OpenLoomi is an open-source desktop AI coworker that connects work tools, gathers context, and highlights decisions or actions needing attention. It is for people managing work across multiple apps, and its catalogue add-ons extend the resident desktop for agent frameworks such as Claude Code, Codex, OpenCode, Hermes, and OpenClaw.

melandlabs/openloomi · 1,022 stars · on GitHub · openloomi.ai

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 melandlabs/openloomi --skill pdf
Clone the repo
git clone --depth 1 https://github.com/melandlabs/openloomi

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/melandlabs/openloomi/pdf.svg)](https://agentmods.dev/skills/melandlabs/openloomi/pdf)
Your own site
<a href="https://agentmods.dev/skills/melandlabs/openloomi/pdf"><img src="https://agentmods.dev/badge/skills/melandlabs/openloomi/pdf.svg" alt="Measured on agentmods" height="20"></a>
Per session 92 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,109 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 92% 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 5.1 $0.00092 $0.02109
Opus 5 $0.00046 $0.01055
Sonnet 5 $0.00018 $0.00422
Haiku 4.5 $0.00009 $0.00211

Measured 8d ago against content hash a2d4f7fa1246, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, 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 8d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/check_bounding_boxes.py, scripts/check_fillable_fields.py, scripts/convert_pdf_to_images.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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

92% identical to pdf — 57 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 · 332 lines

How it starts

The opening of the file, as written. The whole thing — 332 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Processing Guide

Overview

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see REFERENCE.md. If you need to fill out a PDF form, read FORMS.md and follow its instructions.

Quick Start

from pypdf import PdfReader, PdfWriter

# Read a PDF
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")

# Extract text
text = ""
for page in reader.pages:
    text += page.extract_text()

Python Libraries

pypdf - Basic Operations

Merge PDFs
from pypdf import PdfWriter, PdfReader

writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
    reader = PdfReader(pdf_file)
    for page in reader.pages:
        writer.add_page(page)

with open("merged.pdf", "wb") as output:
    writer.write(output)
Split PDF
reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
    writer = PdfWriter()
    writer.add_page(page)
    with open(f"page_{i+1}.pdf", "wb") as output:
        writer.write(output)
Extract Metadata
reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Subject: {meta.subject}")
print(f"Creator: {meta.creator}")
Rotate Pages
reader = PdfReader("input.pdf")
writer = PdfWriter()

page = reader.pages[0]
page.rotate(90)  # Rotate 90 degrees clockwise
writer.add_page(page)

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

pdfplumber - Text and Table Extraction

Extract Text with Layout
import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)
Extract Tables
with pdfplumber.open("document.pdf") as pdf:
    for i, page in enumerate(pdf.pages):
        tables = page.extract_tables()
        for j, table in enumerate(tables):
            print(f"Table {j+1} on page {i+1}:")
            for row in table:
                print(row)

Read the full file on GitHub · 332 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 · 332 lines · 92 tokens per session scan A a2d4f7fa1246

Subscribe to this mod's changes

pdf is a skill published in the GitHub repository melandlabs/openloomi (1,022 stars, last pushed 7d ago), licensed Apache-2.0. It adds 92 tokens to every session and 2,109 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to pdf, differing in 57 lines, and is treated as a copy.

Related

Other skills, from other repositories

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

nano-pdf

Edit PDFs with natural-language instructions using the nano-pdf CLI.

opensquilla/opensquilla · 17 tokens

liteparse

Use this skill when the user asks to parse, perform multi-format document conversion or spatially extract text from an unstructured file (PDF, DOCX, PPTX, XLSX, images, etc.) locally without cloud dependencies.

synthetic-sciences/openscience · 49 tokens

meta-pdf-intelligence

Use this meta-skill instead of answering directly when the user needs PDF analysis, pasted PDF excerpt analysis, digesting, comparison, or question answering that benefits from multi-skill orchestration across PDF extraction, summarization, cross-document synthesis, traceable evidence indexing, and memory capture.

opensquilla/opensquilla · 63 tokens

meta-research-to-slide-deck

Use this meta-skill instead of answering directly when the user needs a researched presentation, leadership briefing, competitive analysis deck, or source-backed slide outline that benefits from multi-skill orchestration across search, source curation, synthesis, slides, and document export.

opensquilla/opensquilla · 60 tokens

meta-multi-format-export-pack

From one piece of source content, render four deliverables: .docx report, .pptx slides, .xlsx data, and an HTML/PDF public version.

opensquilla/opensquilla · 41 tokens