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paper-to-intuition纸质直觉

Agent Skill

paper-to-intuition 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,137

周安装

46

GitHub Stars

3

下载量

357
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:paper-to-intuition(纸质直觉)
来源仓库:https://github.com/ghostscientist/skills
仓库路径:skills/paper-to-intuition
安装命令:
npx skills add https://github.com/ghostscientist/skills --skill paper-to-intuition
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ghostscientist/skills --skill paper-to-intuition

简介

paper-to-intuition 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 它支持通过关键词、任务场景或来源线索进行信息检索与筛选。
  • 可通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Paper to Intuition

Transform dense academic papers into genuine understanding through layered explanation and visual intuition.

Process

  1. Get the paper - Ask for the arXiv link, PDF, or paper title
  2. Extract the core - Identify the single key insight (one sentence)
  3. Build the ladder - Create explanations at 4 levels
  4. Visualize intuition - Generate interactive diagrams
  5. Stress test understanding - "What breaks if we remove X?"

The Explanation Ladder

Generate explanations at each level, with each building on the last:

Level 1: ELI5 (1 paragraph)

  • No jargon, no equations
  • Use familiar analogies from everyday life
  • A curious 10-year-old should roughly get it

Level 2: Undergraduate (2-3 paragraphs)

  • Assume calculus, basic linear algebra, intro ML
  • Introduce key terms with definitions
  • Connect to textbook concepts they'd know

Level 3: Graduate (3-4 paragraphs)

  • Assume ML fundamentals, optimization, probability
  • Discuss relationship to prior work
  • Explain why naive approaches don't work
  • Cover the key equations with plain-English annotations

Level 4: Researcher (2-3 paragraphs)

  • Assume field expertise
  • Subtle technical contributions
  • Limitations and open questions
  • How this changes what's possible

Key Equations Breakdown

For each important equation:

[Equation in LaTeX]

In words: [Plain English translation]

Each term:
- [symbol]: [what it represents] [why it's there]

Intuition: [Why this mathematical form? What would change if we used a different form?]

Visual Intuition Artifact

Generate a self-contained HTML file with:

  • Architecture diagram - Boxes and arrows showing information flow
  • Interactive sliders - Manipulate key parameters, see effects
  • Before/after comparisons - What the method improves over baselines
  • Failure case visualization - When and why it breaks down

Use SVG for diagrams, vanilla JavaScript for interactivity. Dark theme, clean typography.

<!DOCTYPE html>
<html>
<head>
  <title>[Paper Name] - Visual Intuition</title>
  <style>
    :root { --bg: #1a1a2e; --text: #eee; --accent: #4f8cff; }
    /* Clean, research-aesthetic styling */
  </style>
</head>
<body>
  <h1>[Paper Title]</h1>
  <p class="tldr">[One-sentence insight]</p>

  <section id="architecture">
    <svg><!-- Information flow diagram --></svg>
  </section>

  <section id="interactive">
    <!-- Parameter sliders with live updates -->
  </section>

  <section id="comparisons">
    <!-- Before/after, ablations -->
  </section>
</body>
</html>

The "What Breaks?" Analysis

For each major component, explain:

  1. What it does - The role this component plays
  2. What breaks without it - Concrete failure mode
  3. Why this solution - Alternatives considered, why this won
  4. The tradeoff - What we pay for this choice (compute, complexity, assumptions)

Output Structure

Deliver as a structured document:

# [Paper Title]

**TL;DR:** [One sentence]

**Why it matters:** [One paragraph on significance]

## The Explanation Ladder

### ELI5
[...]

### Undergraduate Level
[...]

### Graduate Level
[...]

### Researcher Level
[...]

## Key Equations

### Equation 1: [Name]
[Breakdown as specified above]

## What Breaks If We Remove...

### [Component 1]
[Analysis]

### [Component 2]
[Analysis]

## Visual Intuition

[Link to or embed HTML artifact]

## Further Reading

- [Prerequisite paper 1]
- [Follow-up work 1]

Quality Standards

  • Every analogy must be accurate, not just catchy
  • Equations must be explained, not just translated
  • Visuals must reveal structure, not just decorate
  • The researcher-level section should contain insight, not just summary
  • Admit when something is genuinely confusing or poorly explained in the original paper

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.08%
按下载量换算125

Claude

29%
按下载量换算104

Cursor

19.24%
按下载量换算69

Gemini CLI

8.98%
按下载量换算32

安全审计

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Socket

通过

Snyk

可疑

权限和风险

权限需确认

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安装前确认

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来源信息

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