paper-reader

A workflow for closely studying academic papers from PDF files and turning them into structured HTML notes with extracted text and images. It is designed to explain research so that readers outside the field can understand and repeat the main ideas.

In plain words
What is it for?
Use it to deeply read papers, extract their figures and text, and create image-rich HTML notes for research review.
Why use it?
It removes the need to manually extract figures, organize notes, and turn a difficult paper into a usable explanation. Papers can be processed by ISO week from configured folders.

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/ethan2409/paperflow/paper-reader
Any agent
npx skills add Ethan2409/PaperFlow --skill paper-reader
Clone the repo
git clone --depth 1 https://github.com/Ethan2409/PaperFlow

Made for: Claude Code, Codex.

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,637 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 $0.00069 $0.03637
Opus 5 $0.00034 $0.01818
Sonnet 5 $0.00014 $0.00727
Haiku 4.5 $0.00007 $0.00364

Measured 2d ago against content hash d477c8567eea, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

paper-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 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (assets/extract_figures.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.

paper-reader/SKILL.md · 326 lines

How it starts

The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paper Reader: 文献精读与认知重构

读论文不是做摘要,是猎取思想。本Skill把PDF论文拆解成「不懂这个领域的聪明人也能看懂并复述」的认知框架,最终输出带图片的结构化HTML精读笔记。


前置步骤:读取配置

开始前先读取项目根目录下的 config.yaml(如不存在则读取 config.example.yaml 并提示用户复制修改)。从配置中获取:

  • paths.python_exe — Python 解释器路径
  • literature.pdf_dir — PDF 论文存放目录(按 W{周号}/ 子目录组织)
  • literature.html_output_dir — 精读 HTML 输出目录(按 W{周号}/ 子目录组织)

路径约定

用途 路径 说明
PDF输入 {literature.pdf_dir}/W{周号}/ 按ISO周号组织,如 W24。从 config.yaml 读取 pdf_dir
HTML输出 {literature.html_output_dir}/W{周号}/ 自动创建对应周目录。从 config.yaml 读取
图片资源 {输出目录}/{论文名}_assets/ 与HTML同目录下的assets子目录
提取工具 <SKILL_DIR>/assets/extract_figures.py PDF文字+图片提取脚本

周号规则:默认使用当前ISO周号(python -c "import datetime; print(datetime.date.today().isocalendar()[1])")。用户可指定周号,如"处理W19的所有论文"。

路径说明:所有路径通过项目根目录的 config.yaml 集中配置。安装后请复制 config.example.yamlconfig.yaml 并修改其中的路径为你本机的实际路径。详见项目 README.md 的"安装与配置"章节。


触发条件

用户消息包含以下任一关键词时触发:

  • "精读论文" / "文献精读" / "paper reader" / "paper reading"
  • "读这篇论文" / "解析文献" / "拆解这篇文献"
  • "处理本周文献" / "处理W{数字}的论文"

工作流(严格按此顺序执行)

Phase 1: 确定范围并扫描

  1. 确定周号

    • 若用户未指定,用 python -c "import datetime; print(datetime.date.today().isocalendar()[1])" 获取当前周
    • 格式化为 W{周号}(如 W24
  2. 扫描PDF

    • lsGet-ChildItem 列出 {literature.pdf_dir}/W{周号}/*.pdf
    • 若无PDF文件,告知用户并结束
    • 向用户展示待处理清单,请求确认后再继续
  3. 创建输出目录

    • mkdir -p "{literature.html_output_dir}/W{周号}"

Phase 2: 逐篇处理循环

对每个PDF文件,按以下子步骤执行:

2a. 提取文字 + 图片

运行提取脚本:

"{python_exe}" \
  "<SKILL_DIR>/assets/extract_figures.py" \
  --pdf "{literature.pdf_dir}/W{周号}/{论文文件名}.pdf" \
  --output-dir "{literature.html_output_dir}/W{周号}/{论文名}_assets"

脚本输出:

  • {论文名}_meta.json — 元数据(full_text, figures列表)
  • 提取的图片文件(fig_1.png, fig_2_rendered.png 等)

读取 _meta.json 获取 full_text 和 figures 信息。

扫描版PDF检测(必须执行):读取 _meta.json 后,检查 text_length。如果 text_length < 500(意味着几乎所有页面都无文字层,是扫描图片版PDF),立即停止处理该篇,告知用户:

"这篇「{论文名}」是扫描图片版PDF,fitz 无法提取文字(仅 {text_length} 字符)。请替换为文字版PDF后重试。"

  • 跳过该篇,继续处理列表中下一篇
  • 严禁尝试OCR、渲染页面截图等任何降级方案——这些不可靠且浪费时间

Read the full file on GitHub · 326 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. 2d ago First seen · 326 lines · 69 tokens per session scan A d477c8567eea

Subscribe to this mod's changes

paper-reader is a skill published in the GitHub repository Ethan2409/PaperFlow (9 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 3,637 once invoked, about $0.0003 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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