pdf-reader

pdf-reader is a skill for Claude Code, Codex from ThreeFish-AI/negentropy. It costs 41 tokens per session (1,462 once invoked), scanned A, original, Apache-2.0.

A PDF-processing tool that converts documents into Markdown, a plain-text format used for structured notes and documentation. It can preserve headings, lists, tables, formulas, images, page numbers, and document details.

In plain words
What is it for?
Use it to extract text, images, tables, mathematical formulas, and metadata from one or many PDFs, including selected page ranges.
Why use it?
It removes the manual work of copying structured content from PDFs while keeping important document organization.

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/threefish-ai/negentropy/pdf-reader
Any agent
npx skills add ThreeFish-AI/negentropy --skill pdf-reader
Clone the repo
git clone --depth 1 https://github.com/ThreeFish-AI/negentropy

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-reader

README.md
[![agentmods](https://agentmods.dev/badge/skills/threefish-ai/negentropy/pdf-reader.svg)](https://agentmods.dev/skills/threefish-ai/negentropy/pdf-reader)
Your own site
<a href="https://agentmods.dev/skills/threefish-ai/negentropy/pdf-reader"><img src="https://agentmods.dev/badge/skills/threefish-ai/negentropy/pdf-reader.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,462 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 $0.00041 $0.01462
Opus 5 $0.00020 $0.00731
Sonnet 5 $0.00008 $0.00292
Haiku 4.5 $0.00004 $0.00146

Measured 4d ago against content hash 66ab982a1a40, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pdf-reader 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 4d 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.

.agent/skills/pdf-reader/SKILL.md · 256 lines

How it starts

The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Reader

专门处理 PDF 文档的内容提取,保持原文档的结构和格式。

核心功能

1. 内容提取

  • 文本内容: 保留原始排版和格式
  • 图片资源: 高质量提取并保存
  • 表格数据: 转换为 Markdown 表格格式
  • 数学公式: 保留 LaTeX 格式
  • 元数据: 标题、作者、创建时间等

2. 结构保持

  • 维持文档的章节结构
  • 保留页面编号(如需要)
  • 保持标题层级关系
  • 维护列表和引用格式

Workflow

单文档处理

使用 data-extractor.convert_pdf_to_markdown

参数配置:
  extract_images: true # 提取图片
  extract_tables: true # 提取表格
  extract_formulas: true # 提取公式
  embed_images: false # 图片保存为独立文件
  include_metadata: true # 包含文档元数据

批量文档处理

使用 data-extractor.batch_convert_pdfs_to_markdown

  • 支持多个 PDF 文件同时处理
  • 保持每个文档的独立性
  • 统一的输出格式

页面范围处理(批次支持)

  • 指定页面范围:[start, end]
  • 支持非连续页面处理
  • 用于预览或选择性提取
  • 批次处理时指定具体页面段

图片处理流程

1. 图片提取

  • 自动识别文档中的所有图片
  • 保持原始分辨率
  • 支持多种图片格式

2. 图片分析

使用 zai-mcp-server 分析图片内容:

  • 理解图片描述
  • 生成合适的文件名
  • 创建 alt 文本

3. 图片保存

  • 保存路径:/path/to/source/images/pdf_name/
  • 命名规则:figure_{N}_{description}.png
  • 文件名使用英文,简短且具有描述性

输出格式

Markdown 内容结构

# 文档标题

## 元数据

- **标题**: {title}
- **作者**: {author}
- **页数**: {page_count}
- **创建时间**: {creation_date}

## 内容

![Figure 1: 图片描述](../images/pdf_name/figure_1_diagram.png)

### 1. 章节标题

章节内容...

| 表格标题 |
| -------- |
| 内容     |

$$
  数学公式
$$

返回数据结构

{
  "success": true,
  "content": "Markdown 格式的内容",
  "metadata": {
    "title": "文档标题",
    "author": "作者",
    "page_count": 150,
    "creation_date": "2025-01-01"
  },
  "assets": {
    "images": [
      {
        "filename": "figure_1_diagram.png",
        "path": "../images/pdf_name/figure_1_diagram.png",
        "description": "系统架构图"
      }
    ],
    "tables": 5,
    "formulas": 12
  },
  "statistics": {
    "total_words": 15000,
    "total_paragraphs": 80,
    "processing_time": "2.5s"
  }
}

使用示例

基本用法

提取这个 PDF 的内容:/path/to/document.pdf

指定页面范围

提取 PDF 的第 10-20 页:/path/to/document.pdf [10, 20]

批量处理

批量处理这些 PDF:
- /path/to/doc1.pdf
- /path/to/doc2.pdf
- /path/to/doc3.pdf

高级选项

提取 PDF 内容,需要包含所有图片和表格,但不提取公式:/path/to/document.pdf

Read the full file on GitHub · 256 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. 4d ago First seen · 256 lines · 41 tokens per session scan A 66ab982a1a40

Subscribe to this mod's changes

pdf-reader is a skill published in the GitHub repository ThreeFish-AI/negentropy (10 stars, last pushed 4d ago), licensed Apache-2.0. It adds 41 tokens to every session and 1,462 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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