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Paper Analysis Assistant

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anbeime
paper-analysis-assistant

其他高等院校教师与数据科学家在追踪前沿学术时,当需要深度解析arXiv论文,用此技能可一键下载PDF并自动生成词频分析、双人播客、交互式网页、PPT演示与总结图,将数小时的文献阅读转化为多媒体内容,效率提升十倍!

Overview

Publisheranbeime
Repositoryskill
Skill namepaper-analysis-assistant
Stars
6.9K
Forks
645
Bundled files
9
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by anbeime on GitHub. Read the source before you install it.

Installation

Install the Paper Analysis Assistant AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anbeime/skill.git /tmp/skill
mkdir -p .claude/skills
cp -r /tmp/skill/skills/paper-analysis-assistant/paper-analysis-assistant .claude/skills/paper-analysis-assistant
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Analysis Assistant in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Paper Analysis Assistant on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Paper Analysis Assistant is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

论文分析助手

任务目标

  • 本 Skill 用于:根据 arXiv 论文网址自动进行多维度分析并生成多种格式的输出
  • 能力包含:PDF 下载与文本提取、词频统计、语音合成、播客对话生成、交互式网页、PPT 生成、总结图生成、引用分析
  • 触发条件:用户提供 arXiv 论文网址或论文 PDF 文件

前置准备

  • 依赖说明:所需 Python 包已在 dependency 中列出
  • 停用词资源:需准备英文停用词列表,用于词频分析过滤

操作步骤

  • 标准流程:

    1. 下载 PDF 文件
      • 调用 scripts/download_pdf.py 下载 arXiv PDF
      • 参数:--url (arXiv 论文网址), --output (输出 PDF 文件路径)
    2. 提取 PDF 文本
      • 调用 scripts/extract_text.py 提取纯文本
      • 参数:--pdf (PDF 文件路径), --output (输出 txt 文件路径)
    3. 词频分析
      • 调用 scripts/analyze_word_frequency.py 进行词频统计
      • 参数:--txt (txt 文件路径), --output (输出 csv 文件路径)
      • 该脚本会自动过滤英文停用词(见 references/stopwords.txt)
    4. 文本转语音
      • 调用 scripts/text_to_speech.py 将文本转为语音
      • 参数:--txt (txt 文件路径), --output (输出 wav 文件路径)
    5. 生成播客对话
      • 智能体步骤:根据论文内容生成双人对话脚本(包含两个角色的对话内容)
      • 脚本步骤:调用 scripts/dialogue_to_podcast.py 将对话脚本转换为语音
      • 参数:--dialogue (对话脚本文件路径), --output (输出 wav 文件路径)
    6. 生成交互式网页
      • 调用 scripts/generate_html.py 生成交互式网页
      • 参数:--txt (txt 文件路径), --word_freq (词频 csv 文件路径), --output (输出 html 文件路径)
    7. 生成 PPT
      • 调用 scripts/generate_ppt.py 生成演示文稿
      • 参数:--txt (txt 文件路径), --output (输出 pptx 文件路径)
    8. 生成总结图
      • 智能体步骤:根据论文内容直接生成"一图胜千言"的总结图(PNG 格式)
    9. 分析引用链接
      • 调用 scripts/extract_references.py 提取引用链接
      • 参数:--txt (txt 文件路径), --output (输出 csv 文件路径)
  • 可选分支:

    • 当 用户直接提供 PDF 文件:跳过步骤 1,直接从步骤 2 开始
    • 当 用户只需要部分分析:根据需求选择性执行对应步骤

资源索引

注意事项

  • 确保所有脚本参数路径正确,特别是输入输出文件的相对路径
  • 语音合成功能需要系统支持语音引擎(pyttsx3)
  • 播客对话的脚本内容由智能体生成,需确保对话格式正确
  • 总结图由智能体直接生成,无需调用脚本

使用示例

  • 示例 1:完整分析流程
    bash
    # 下载 PDF
    python scripts/download_pdf.py --url "https://arxiv.org/abs/2301.00001" --output ./user-data/paper.pdf
    # 提取文本
    python scripts/extract_text.py --pdf ./user-data/paper.pdf --output ./user-data/paper.txt
    # 词频分析
    python scripts/analyze_word_frequency.py --txt ./user-data/paper.txt --output ./user-data/word_freq.csv
    # 语音合成
    python scripts/text_to_speech.py --txt ./user-data/paper.txt --output ./user-data/paper.wav
    # 播客对话(智能体生成对话脚本后)
    python scripts/dialogue_to_podcast.py --dialogue ./user-data/dialogue.txt --output ./user-data/podcast.wav
    # 生成网页
    python scripts/generate_html.py --txt ./user-data/paper.txt --word_freq ./user-data/word_freq.csv --output ./user-data/analysis.html
    # 生成 PPT
    python scripts/generate_ppt.py --txt ./user-data/paper.txt --output ./user-data/presentation.pptx
    # 提取引用
    python scripts/extract_references.py --txt ./user-data/paper.txt --output ./user-data/references.csv
  • 示例 2:快速分析(仅词频和引用)
    bash
    python scripts/analyze_word_frequency.py --txt ./user-data/paper.txt --output ./user-data/word_freq.csv
    python scripts/extract_references.py --txt ./user-data/paper.txt --output ./user-data/references.csv

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Paper Analysis Assistant AI skill do?

其他高等院校教师与数据科学家在追踪前沿学术时,当需要深度解析arXiv论文,用此技能可一键下载PDF并自动生成词频分析、双人播客、交互式网页、PPT演示与总结图,将数小时的文献阅读转化为多媒体内容,效率提升十倍!

Why use Paper Analysis Assistant on TypingMind?

Because you install it once and use it with any model. Paper Analysis Assistant is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Paper Analysis Assistant in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anbeime/skill/tree/main/skills/paper-analysis-assistant/paper-analysis-assistant. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Paper Analysis Assistant?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Paper Analysis Assistant?

As many as you like. As long as a model supports skills, you can use Paper Analysis Assistant with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Paper Analysis Assistant AI skill free?

It is published on GitHub by anbeime. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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