Agent skill

Paper Interpreter

by digoal in digoal/blog

深度解读学术论文,将论文 PDF(文件或 URL)转化为通俗易懂、图文并茂的 Markdown 解读文档,保存到项目的 markdown/ 目录。触发条件:用户上传或提供论文 PDF、提到"解读论文"/"读论文"/"分析这篇论文"/"帮我看这篇 paper",或任何需要深入理解一篇学术论文的场景。即使用户只说"帮我看这个 PDF"但内容是论文,也应使用本…

GPL-2.0Auto-check passedDocuments & Office

Install Paper Interpreter

skills CLI
$ npx skills add digoal/blog --skill paper-interpreter -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install digoal/blog paper-interpreter --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skills_for_claude_web/paper-interpreter .claude/skills/paper-interpreter && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
paper-interpreter
GitHub stars
8.6k
Token cost
~1.1k tokens
SKILL.md length
189 words
Files
2
Skills in repo
98
Repo updated
First seen
Licence
GPL-2.0

At a glance

深度解读学术论文,将论文 PDF(文件或 URL)转化为通俗易懂、图文并茂的 Markdown 解读文档,保存到项目的 markdown/ 目录。触发条件:用户上传或提供论文 PDF、提到"解读论文"/"读论文"/"分析这篇论文"/"帮我看这篇 paper",或任何需要深入理解一篇学术论文的场景。即使用户只说"帮我看这个 PDF"但内容是论文,也应使用本…

  • Works in 4 steps: :获取论文内容 → :确定输出路径 → :执行五步解读法,生成 Markdown → …
  • Tasks that involve Diagrams
  • SKILL.md covers 工作流程总览, Step 0:获取论文内容, Step 1:确定输出路径 and Step 2:执行五步解读法,生成 Markdown, plus 3 more sections
  • Calls pip and python3

What it does

Paper Interpreter is an agent skill from digoal/blog. 深度解读学术论文,将论文 PDF(文件或 URL)转化为通俗易懂、图文并茂的 Markdown 解读文档,保存到项目的 markdown/ 目录。触发条件:用户上传或提供论文 PDF、提到"解读论文"/"读论文"/"分析这篇论文"/"帮我看这篇 paper",或任何需要深入理解一篇学术论文的场景。即使用户只说"帮我看这个 PDF"但内容是论文,也应使用本 skill。输出文件包含:论文定位、知识地图、5W1H精读、术语词典、批判性评估五大板块,并在关键位置插入 mermaid/svg/text 图表辅助理解。

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in Documents & Office, covering Diagrams, PDF and Markdown. It works with Mermaid. The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.

When your agent uses it

  • Tasks that involve Diagrams
  • Tasks that involve PDF
  • Tasks that involve Markdown

Example prompts

  • “分析这篇论文”
  • “帮我看这篇 paper”
  • “帮我看这个 PDF”
  • “/paper-interpreter”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. :获取论文内容
  2. :确定输出路径
  3. :执行五步解读法,生成 Markdown
  4. :写入文件

What it can do on your machine

Read from SKILL.md and the folder at commit 69fb793. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Paper Interpreter loads about 1.1k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 189 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from digoal/blog at commit 69fb793, republished under its GPL-2.0 licence (© digoal). 189 words, ~1,087 tokens.

Download SKILL.mdSave it as .claude/skills/paper-interpreter/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
paper-interpreter
description
深度解读学术论文,将论文 PDF(文件或 URL)转化为通俗易懂、图文并茂的 Markdown 解读文档,保存到项目的 markdown/ 目录。触发条件:用户上传或提供论文 PDF、提到"解读论文"/"读论文"/"分析这篇论文"/"帮我看这篇 paper",或任何需要深入理解一篇学术论文的场景。即使用户只说"帮我看这个 PDF"但内容是论文,也应使用本 skill。输出文件包含:论文定位、知识地图、5W1H精读、术语词典、批判性评估五大板块,并在关键位置插入 mermaid/svg/text 图表辅助理解。

Paper Interpreter Skill

将学术论文转化为通俗易懂、图文并茂的深度解读文档。

工作流程总览

输入(PDF文件/URL) → 全文提取 → 5步解读 → 输出 Markdown 文件到 markdown/

Step 0:获取论文内容

情况A:用户上传了 PDF 文件

读取路径 /mnt/user-data/uploads/ 下的 PDF 文件,用 bash_tool 提取文本:

bash
pip install pdfminer.six --break-system-packages -q
python3 - <<'EOF'
from pdfminer.high_level import extract_text
text = extract_text("/mnt/user-data/uploads/论文文件名.pdf")
print(text[:50000])  # 先输出前50000字符
EOF

若论文有图表密集或文字提取不完整,追加用 pymupdf 逐页提取并描述图表内容:

bash
pip install pymupdf --break-system-packages -q
python3 - <<'EOF'
import fitz
doc = fitz.open("/mnt/user-data/uploads/论文文件名.pdf")
for i, page in enumerate(doc):
    print(f"\n=== Page {i+1} ===")
    print(page.get_text())
    # 列出图片
    imgs = page.get_images()
    if imgs:
        print(f"[此页含 {len(imgs)} 张图片]")
EOF
情况B:用户提供了 PDF URL

使用 web_fetch 工具抓取 PDF,或者先用 web_search 找到 arXiv/DOI 页面,再抓取 HTML 摘要 + 全文。

web_fetch(url)  →  提取文本内容

重要:提取完成后,记录以下信息备用:

  • 论文标题、作者、发表年份、期刊/会议
  • 摘要(Abstract)
  • 章节结构
  • 所有图表的标题和描述
  • 实验数据和核心结论

Step 1:确定输出路径

bash
mkdir -p markdown
# 文件名格式:论文标题关键词(英文)+ _解读.md
# 例:attention_is_all_you_need_解读.md

Step 2:执行五步解读法,生成 Markdown

按以下结构逐步撰写输出文档。每一步都必须完成,不可跳过。


📍 第0步:论文定位

目标:让读者在30秒内判断"这篇论文值不值得读、跟我有什么关系"。

写法要求:

  1. 一句话摘要:用最简单的语言说清楚这篇论文做了什么
  2. 价值标注:
    • 🎓 学术价值:在学界填补了什么空白 / 突破了什么瓶颈
    • 🏭 工业价值:在业界可以用来做什么、解决什么实际问题
  3. 直觉类比:用一个生活化的类比帮助读者建立第一印象

示例格式:

markdown
## 📍 论文定位

**一句话**:本文提出了 XXX 方法,解决了 YYY 场景下 ZZZ 的问题。

**🎓 学术价值**:首次将...应用于...领域,填补了...的空白。

**🏭 工业价值**:可直接用于...系统,降低...成本,提升...效率。

**💡 直觉类比**:这篇论文就像是给 AI 配了一个...,让它能够...

🗺️ 第1步:知识地图

目标:用结构化方式呈现读懂本文所需的前置知识,降低阅读门槛。

写法要求:

  1. 用 Mermaid 图 画出知识树(三层:核心→支撑→扩展)
  2. 对每个核心概念,用「是什么 + 为什么重要 + 现实类比」三件套讲解
  3. 标注难度等级(⭐ 简单 / ⭐⭐ 中等 / ⭐⭐⭐ 较难)

Mermaid 知识树模板:

mermaid
graph TD
    A[读懂本文需要] --> B[核心概念 必须懂]
    A --> C[支撑概念 有助理解]
    A --> D[扩展概念 感兴趣再看]
    B --> B1[概念1 ⭐⭐]
    B --> B2[概念2 ⭐⭐⭐]
    C --> C1[概念3 ⭐]
    D --> D1[概念4 ⭐⭐]

🔬 第2步:论文精读(5W1H框架)

目标:按"问题-方案-验证"三段式完整解读论文内容。

2.1 Why — 为什么要做这个研究?
  • 现有方法的痛点是什么?
  • 作者的 motivation 是什么?
  • 用对比表格展示"之前 vs 本文"
2.2 What — 提出了什么方法/系统?
  • 核心方法/架构是什么?
  • 用 Mermaid 流程图或架构图 展示系统结构
  • 如果论文有架构图,用文字 + mermaid 重新描述

Mermaid 架构图示例:

mermaid
graph LR
    输入 --> 模块A
    模块A --> 模块B
    模块B --> 模块C
    模块C --> 输出
2.3 How — 具体怎么实现的?
  • 关键技术细节(公式可以保留,但必须加白话解释)
  • 重要的设计选择和背后的直觉
  • 如有伪代码/算法,用代码块呈现并注释
2.4 So What — 结果怎么样?
  • 主要实验结果(用表格整理核心指标对比)
  • 消融实验说明了什么?
  • 结果中最令人印象深刻的发现是什么?
2.5 Now What — 对我们意味着什么?
  • 学术界:开了哪些新方向?
  • 工业界:可以怎么落地?有哪些应用场景?

📖 第3步:术语词典

目标:让读者看完就记住关键术语的含义和重要性。

每个术语使用固定三件套模板:

markdown
### 术语名(英文原名)
- **是什么**:...
- **为什么重要**:...
- **现实类比**:就像...

只收录论文中真正关键的术语(5~15个),不要堆砌所有专业词汇。


⚖️ 第4步:批判性评估

目标:培养读者的独立思考能力,呈现论文的局限性与未来方向。

必须覆盖以下四个维度:

  1. 假设前提的合理性

    • 论文依赖哪些假设?
    • 这些假设在现实场景中是否成立?
  2. 实验设计的可质疑之处

    • 基线选择是否公平?
    • 数据集是否有代表性?
    • 有没有重要的对比实验缺失?
  3. 方法的适用边界

    • 这个方法在什么场景下会失效?
    • 有哪些已知限制(计算成本、数据依赖、场景限制等)?
  4. 未来改进方向

    • 作者自己提出的 future work 是什么?
    • 读者/你认为还可以从哪些角度改进?

Step 3:写入文件

完整的 Markdown 文件结构如下:

markdown
# 📄 论文解读:{论文标题}

> **原文信息**:作者 | 年份 | 期刊/会议
> **解读日期**:{今天日期}

---

## 📍 论文定位
...

---

## 🗺️ 知识地图
...

---

## 🔬 论文精读
### Why — 研究动机
### What — 核心方法
### How — 技术细节
### So What — 实验结果
### Now What — 价值总结

---

## 📖 术语词典
...

---

## ⚖️ 批判性评估
...

---

## 📚 参考资料
- 原文链接
- 相关论文(如论文中引用的关键文献)

最后执行:

bash
# 保存文件
cp /home/claude/解读文件.md markdown/文件名.md
echo "✅ 解读文档已保存至 markdown/文件名.md"

质量检查清单

生成文档后,逐项确认:

  • 包含至少 1 个 Mermaid 图(知识树或架构图)
  • 包含至少 1 个对比表格(方法对比或实验结果)
  • 每个核心概念都有现实类比
  • 术语词典覆盖 5 个以上关键术语
  • 批判性评估覆盖全部 4 个维度
  • 文件已保存到 markdown/ 目录
  • 文档语言通俗,无堆砌定义的段落

常见注意事项

关于图片:论文中的图片无法直接嵌入 Markdown,应用文字描述 + mermaid 重新表达其核心信息。

关于公式:保留核心公式(使用 LaTeX 格式 $公式$),但每个公式后面必须跟一段白话解释。

关于篇幅:解读文档通常在 2000~5000 字之间。太短说明解读不够深入,太长可能存在不必要的堆砌。

关于语气:用"我们"和"读者"的视角写作,像一位熟悉该领域的朋友在讲解,避免学术腔。

© digoal, GPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/skills_for_claude_web/paper-interpreter of digoal/blog.

  • SKILL.md
  • paper-interpreter.skill

Open the folder on GitHubat commit 69fb793

Compare with similar skills

Paper Interpreter next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Paper Interpreter compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Paper Interpreter this skilldigoal/blog8.6k—~1.1kAutomated safety check: PassGPL-2.0
Ky Markdown RebuilderKyrieCheungYep/ky-markdown-rebuilder117—~5.7kAutomated safety check: PassNone
Paper Interpreterchujianyun/skills740—~810Automated safety check: PassCustom licence
Bangunai Blog ManagerLeoYeAI/openclaw-master-skills2.2k—~5.7kAutomated safety check: PassMIT
Markdown Syntax Guideantdigital-ai/agentic-ui224—~3.1kAutomated safety check: PassMIT
Markdown Report WritingNeuroAIHub/BrainPilot1.1k—~2.6kAutomated safety check: WarnAGPL-3.0

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Works with

Questions about Paper Interpreter

What does Paper Interpreter do?

深度解读学术论文,将论文 PDF(文件或 URL)转化为通俗易懂、图文并茂的 Markdown 解读文档,保存到项目的 markdown/ 目录。触发条件:用户上传或提供论文 PDF、提到"解读论文"/"读论文"/"分析这篇论文"/"帮我看这篇 paper",或任何需要深入理解一篇学术论文的场景。即使用户只说"帮我看这个 PDF"但内容是论文,也应使用本…. Paper Interpreter is an agent skill from digoal/blog.

When should I use Paper Interpreter?

Paper Interpreter fits situations like: tasks that involve Diagrams; tasks that involve PDF; tasks that involve Markdown.

How do I install Paper Interpreter in Claude Code?

Run `npx skills add digoal/blog --skill paper-interpreter -a claude-code`. Or copy the skill folder (skills/skills_for_claude_web/paper-interpreter in digoal/blog) into .claude/skills/paper-interpreter in your project. Claude Code loads it when a task matches its description.

How do I install Paper Interpreter in Codex?

Run `npx skills add digoal/blog --skill paper-interpreter -a codex`. Or copy the skill folder (skills/skills_for_claude_web/paper-interpreter in digoal/blog) into .agents/skills/paper-interpreter in your project. Codex loads it when a task matches its description.

Can I use Paper Interpreter in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add digoal/blog --skill paper-interpreter -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paper-interpreter, .gemini/skills/paper-interpreter, .github/skills/paper-interpreter and .opencode/skills/paper-interpreter in your project.

What does Paper Interpreter need to run?

Going by SKILL.md and its folder, Paper Interpreter needs the command-line tools its instructions call (pip and python3). Our summary lists: Python 3.

Does Paper Interpreter access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Paper Interpreter safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Paper Interpreter use?

Paper Interpreter is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Paper Interpreter use?

About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Paper Interpreter?

Skills that share tags, products or a category with Paper Interpreter: Ky Markdown Rebuilder (KyrieCheungYep/ky-markdown-rebuilder, 117 stars), Paper Interpreter (chujianyun/skills, 740 stars), Bangunai Blog Manager (LeoYeAI/openclaw-master-skills, 2.2k stars) and Markdown Syntax Guide (antdigital-ai/agentic-ui, 224 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Paper Interpreter?

digoal (a GitHub user) maintains it in digoal/blog, which has 8,587 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on September 28, 2026.

Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.