oma-pdf

oma-pdf is a skill for Claude Code, Codex from gracefullight/docusaurus-plugins. It costs 52 tokens per session (1,749 once invoked), scanned A, a copy of oma-pdf, MIT.

A PDF-to-Markdown converter that extracts text, headings, lists, tables, images, footnotes, and links while keeping their reading order. Markdown is plain text with simple formatting that works well in code and AI tools.

In plain words
What is it for?
Use it to parse PDFs, extract tables and images, prepare documents for AI or retrieval systems, and check whether a PDF has usable text before choosing OCR.
Why use it?
It turns PDF content into structured, AI-ready text instead of leaving information trapped in a layout designed mainly for visual reading.

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/gracefullight/docusaurus-plugins/oma-pdf
Any agent
npx skills add gracefullight/docusaurus-plugins --skill oma-pdf
Clone the repo
git clone --depth 1 https://github.com/gracefullight/docusaurus-plugins

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 oma-pdf

README.md
[![agentmods](https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-pdf.svg)](https://agentmods.dev/skills/gracefullight/docusaurus-plugins/oma-pdf)
Your own site
<a href="https://agentmods.dev/skills/gracefullight/docusaurus-plugins/oma-pdf"><img src="https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-pdf.svg" alt="Measured on agentmods" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,749 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 89% 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 $0.00052 $0.01749
Opus 5 $0.00026 $0.00874
Sonnet 5 $0.00010 $0.00350
Haiku 4.5 $0.00005 $0.00175

Measured yesterday against content hash 51f46c4bff8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

oma-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 yesterday.

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

89% identical to oma-pdf — 15 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.

.agents/skills/oma-pdf/SKILL.md · 160 lines

How it starts

The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Skill - PDF to Markdown Conversion

Scheduling

Goal

Convert PDF files into structured Markdown or another requested extraction format while preserving readable document structure for LLM context, RAG, or downstream review.

Intent signature

  • User asks to convert, parse, read, extract, or transform a PDF.
  • User needs PDF text, headings, lists, tables, or images prepared for AI consumption.
  • User mentions "PDF to markdown", "parse PDF", "read this PDF", or equivalent wording.

When to use

  • Converting PDF documents to Markdown for LLM context or RAG
  • Extracting structured content such as tables, headings, lists, images, footnotes, or hyperlinks
  • Preparing PDF data for AI consumption
  • Checking whether a PDF has a text layer before choosing OCR

When NOT to use

  • Generating or creating PDFs -> use document-generation tools
  • Editing existing PDFs -> out of scope
  • Reading an already-text file -> use direct file reading
  • Processing HWP, HWPX, DOCX, XLSX, or slide decks -> use the matching document skill

Expected inputs

  • input_path: PDF file or folder path
  • output_dir: optional target directory
  • format: optional output format, default markdown
  • ocr_languages: optional OCR language list for scanned or image-based PDFs
  • extraction_options: optional flags for tagged structure, image extraction, or hybrid conversion

Expected outputs

  • Markdown, text, JSON, HTML, or combined extraction output
  • Normalized Markdown when Markdown is produced
  • A short report with output path, page count, and conversion issues

Dependencies

  • uvx opendataloader-pdf for standard conversion
  • uvx --from "opendataloader-pdf[hybrid]" opendataloader-pdf-hybrid for OCR or hybrid conversion (the hybrid server is a console script of the [hybrid] extra, not a standalone package)
  • uvx mdformat for Markdown normalization
  • Local filesystem access to input and output paths
  • Optional OCR runtime via the hybrid server

Control-flow features

  • Branches on text-layer quality, tagged PDF availability, scan/OCR needs, and user-requested output format
  • Calls external CLI tools through uvx
  • Reads local files and writes local extraction outputs
  • Uses a hybrid server only when OCR or complex extraction needs justify it

Read the full file on GitHub · 160 lines

Files

What ships with it

2 files 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. yesterday First seen · 160 lines · 52 tokens per session scan A 51f46c4bff8c

Subscribe to this mod's changes

oma-pdf is a skill published in the GitHub repository gracefullight/docusaurus-plugins (22 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 1,749 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to oma-pdf, differing in 15 lines, and is treated as a copy.

Related

Other skills, from other repositories

Chat with PDF

Answer questions about PDF content, summarize, and extract information.

claude-office-skills/skills · 15 tokens

pdf-skill

PDF 读/写/转/OCR 一体化。触发场景:总结 PDF、读文本或表格、填 AcroForm 表单、渲染页面为图、合并/拆分/水印/旋转/加密、创建新 PDF(发票/报告)、PDF ↔ docx/md/txt 互转。典型说法:“总结这份 PDF”、“填一下这个 PDF 表单”、“把几个 PDF 合一起”、“PDF 加水印”、“PDF 转 Word”、“扫描件 OCR”、“看看 PDF 第 3 页长什么样”。用户提到 .pdf 文件、要产出 PDF、或要对 PDF 做任何改动都加载本技能。.

OpenLoaf/OpenLoaf · 152 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

foundry-hosted-agent-validation

Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.

microsoft/agent-framework · 82 tokens

skill-doc-delivery

Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.

nyldn/claude-octopus · 29 tokens

document-direct-python

Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports.

HKUDS/OpenSpace · 20 tokens