Borrowing it
Nothing to install: this file belongs to ThreeFish-AI/negentropy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ThreeFish-AI/negentropy/master/.agent/skills/pdf-reader/SKILL.mdgit clone --depth 1 https://github.com/ThreeFish-AI/negentropyWrote 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.
[](https://agentmods.dev/skills/threefish-ai/negentropy/pdf-reader)<a href="https://agentmods.dev/skills/threefish-ai/negentropy/pdf-reader"><img src="https://agentmods.dev/badge/skills/threefish-ai/negentropy/pdf-reader/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<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="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01462 |
| Opus 5.5 | $0.00016 | $0.00585 |
| Sonnet 5.5 | $0.00008 | $0.00292 |
| Haiku 4.5 | $0.00004 | $0.00146 |
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 1mo 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.
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

### 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
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.
- 1mo ago First seen · 256 lines · 41 tokens per session scan A 66ab982a1a40
pdf-reader is a skill published in the GitHub repository ThreeFish-AI/negentropy (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 41 tokens to every session and 1,462 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
literature
Load when extracting GEO accessions, dataset metadata, and downloadable references from a scientific paper (PDF / URL / DOI / PubMed ID / raw text) for downstream omics analysis. Skip when the dataset is already in hand; the paper names no dataset to fetch.
potpie-resource-pdf
Use when the user asks to ingest a PDF (report, contract, paper, manual, slide export) into Potpie so agents can search and cite it. Teaches the extraction-script flow: resolve the document's identity, split on the PDF's own structure into sections and 4k-char chunks, import with potpie resource import, write…
wechat-article-ingest
A tool that converts public WeChat Official Account articles, or PDF copies of them, into Markdown notes. It can also extract the article's main viewpoints and create linked questions for further thinking.
paper-writing
Write and typeset formal documents — academic papers, reports, articles — using Markdown + Pandoc and LaTeX. Convert between formats (md↔pdf↔docx↔tex), manage citations with BibTeX/CSL. Keyless, local. Use when asked to "write a paper", "format this as LaTeX", "convert to PDF/Word", "add citations".
pdf-tools
Manipulate PDFs locally — merge, split, extract pages, rotate, compress, extract text, convert images↔PDF. Uses keyless local CLIs (pdftk/qpdf/pdftotext/poppler/img2pdf/Ghostscript). Use when asked to "merge PDFs", "split this PDF", "extract text from PDF", "compress PDF", "PDF to images".
resume-tailor
Rewrite a candidate's resume tailored to one specific JD using a hiring-recon report, emit it as a rendercv YAML, then render to PDF. Reorders jobs/bullets and adjusts language to incorporate JD keywords without inventing experience. Outputs one YAML (source of truth, user-editable) plus a .pdf published alongside it.