/claude-paper-summary

name: claude-paper-summary
description: Use this for a quick summary of a research paper's core ideas and key points. Use when you want to quickly understand a paper without deep study materials. Triggers on PDF paths, arXiv URLs, or paper URLs.
allowed-tools: Bash, Write, Read

Cross-Agent Compatibility

> This file is generated from the existing Claude Paper Skill. Its workflow and output requirements are unchanged; only equivalent host metadata, the plugin-root variable, and cross-skill invocation are adapted.

Resolve `CLAUDE_PAPER_PLUGIN_ROOT` to the absolute `plugin/` directory in this package before each shell invocation. From this `SKILL.md`, that directory is `../../plugin`. Treat every `${CLAUDE_PAPER_PLUGIN_ROOT}` reference below as that resolved absolute directory. Do not substitute the current workspace root.

When this workflow asks to launch the viewer, load and follow the `claude-paper-webui` skill.

---

Quick Paper Summary Workflow

This skill generates a **concise summary** of a research paper's core ideas and key points.

**When to use:**

• You want to quickly understand what a paper is about
• You need the main contributions without deep technical details
• You're screening papers to decide which to study in depth

**When NOT to use:**

• You want comprehensive study materials (use `claude-paper-study` skill instead)
• You need code demonstrations
• You want interactive visualizations

---

**Language Detection**: Detect the user's language from their input and generate ALL materials in that language.

• Example: User says "我们学习一下这篇论文" → Generate materials in Chinese
• Example: User says "Let's study this paper" → Generate materials in English

---

Step 0: Check Dependencies (First Run Only)

if [ ! -f "${CLAUDE_PAPER_PLUGIN_ROOT}/.installed" ]; then
  echo "First run - installing dependencies..."
  cd "${CLAUDE_PAPER_PLUGIN_ROOT}"
  npm install || exit 1

  # Install Python dependencies for image extraction
  python3 -m pip install pymupdf --user 2>/dev/null || pip3 install pymupdf --user 2>/dev/null || echo "Warning: Failed to install pymupdf"

  touch "${CLAUDE_PAPER_PLUGIN_ROOT}/.installed"
  echo "Dependencies installed!"
fi

---

Step 1: Download and Parse PDF

Supports multiple input formats:

• **Local path**: `~/Downloads/paper.pdf`
• **Direct PDF URL**: `https://arxiv.org/pdf/1706.03762.pdf`
• **arXiv URL**: `https://arxiv.org/abs/1706.03762`

Step 1a: Check input type and download if URL

USER_INPUT="<user-input>"

# Check if input is a URL (starts with http:// or https://)
if [[ "$USER_INPUT" =~ ^https?:// ]]; then
  # Download PDF from URL
  INPUT_PATH=$(node ${CLAUDE_PAPER_PLUGIN_ROOT}/skills/study/scripts/download-pdf.cjs "$USER_INPUT")
else
  # Use local path directly
  INPUT_PATH="$USER_INPUT"
fi

For URLs, the download script will:

• Download PDFs to `/tmp/claude-paper-downloads/`
• Convert arXiv `/abs/` URLs to PDF URLs automatically
• Validate that URLs point to PDF files
• Return the local file path for processing

Step 1b: Parse PDF

Extract structured information:

PARSE_OUTPUT_DIR=$(mktemp -d)
node ${CLAUDE_PAPER_PLUGIN_ROOT}/skills/study/scripts/parse-pdf.js \
  "$INPUT_PATH" \
  --output-dir "$PARSE_OUTPUT_DIR"

The command prints a small, strict JSON summary to stdout and writes:

• `meta.json` — title, authors, abstract, links, page count, and a context-safe content preview
• `paper.txt` — complete extracted text without the 50k preview limit

Use `paper.txt` as the source for the quick summary. Do not treat `meta.json.content` as the complete paper when `contentTruncated` is true.

---

Step 2: Generate Quick Summary

Create the paper folder:

mkdir -p ~/claude-papers/papers/{paper-slug}
cp "<metaPath-from-parser-output>" ~/claude-papers/papers/{paper-slug}/meta.json
cp "<fullTextPath-from-parser-output>" ~/claude-papers/papers/{paper-slug}/paper.txt
cp "$INPUT_PATH" ~/claude-papers/papers/{paper-slug}/paper.pdf

Generate **quick-summary.md** with the following structure:

# Quick Summary: [Paper Title]

## One Sentence
[One sentence that captures what the paper is about]

## Problem
[What problem does this paper solve? Why is it important?]

## Core Idea
[The key innovation explained in 2-3 sentences. What makes this paper novel?]

## Key Contributions
- [Contribution 1]
- [Contribution 2]
- [Contribution 3]
- [Contribution 4 if applicable]

## Main Results
| Metric | Value | Dataset/Benchmark |
|--------|-------|-------------------|
| [metric1] | [value] | [dataset] |
| [metric2] | [value] | [dataset] |

## Why It Matters
[Practical implications. How does this advance the field? What can we now do that we couldn't before?]

## Limitations
- [Limitation 1]
- [Limitation 2]

**Guidelines for each section:**

| Section | Length | Focus | |---------|--------|-------| | One Sentence | 1 sentence | High-level summary | | Problem | 2-3 sentences | Context and motivation | | Core Idea | 2-3 sentences | The main innovation | | Key Contributions | 3-5 bullets | What's new/novel | | Main Results | 1 table | Quantitative metrics from the paper | | Why It Matters | 2-3 sentences | Practical value | | Limitations | 2-3 bullets | What the paper doesn't solve |

**Total length:** ~300-500 words (excluding results table)

---

Step 3: Update Index

**CRITICAL**: Read existing index.json first, then append the new paper. Never overwrite the entire file.

If index.json does not exist, create:

{"papers": []}

Append new entry to the papers array:

{
  "id": "paper-slug",
  "title": "Paper Title",
  "slug": "paper-slug",
  "authors": ["Author 1", "Author 2"],
  "abstract": "Paper abstract...",
  "year": 2024,
  "date": "2024-01-01",
  "tags": ["quick-summary"],
  "githubLinks": ["https://github.com/..."],
  "codeLinks": ["https://..."]
}

**IMPORTANT**: The index.json file must be located at:

~/claude-papers/index.json

---

Step 4: Rel