Options:
- `--output`, `-o`: Output file path (defaults to stdout)
- `--skip-fulltext`: Extract abstract only (fast mode, skip PDF)
- `--doi`: Explicit DOI
- `--arxiv-id`: Explicit arXiv ID

### Phase 2: Agent reads and writes the summary

Read the extracted JSON section by section (`read` tool with `offset`/`limit` for large files), then write a structured summary JSON to `/tmp/paper_summary.json`.

#### Reading strategy (context management)
- Read Abstract → Introduction → Method → Experiments → Conclusion in order
- For long papers, read in chunks and accumulate understanding
- Focus on: core idea, key equations, experimental setup, main results, ablations

#### Summary JSON template

#### Quality guidelines

1. **Terminology**: Keep technical terms in their original language; explanations in the user's language.
2. **Equations**: Include key equations in LaTeX (`$$ ... $$`).
3. **Depth**: Seminar-presentation level understanding.
   - Method: Not just "they did X" but "why they designed it this way, what each component does"
   - Experiments: Not just "it worked" but "X% improvement over Y baseline under Z conditions"
4. **Critical perspective**: Record limitations and open questions, not just strengths.
5. **Connections**: If you know the user's research interests, connect the paper to them.
6. **No programming code blocks**: Do NOT use fenced code blocks (

Options:
- `--parent-page-id`: Notion page ID to create the summary under
- `--force-update`: Overwrite existing page with same title
- `--dry-run`: Preview without uploading
- `--notion-key`: Explicit Notion API token

## Quick Start (full agent flow)

python3 scripts/extract_paper.py \
  --output /tmp/paper_extract.json \
  "https://arxiv.org/abs/2301.12345"

python3 scripts/extract_paper.py \
  --output /tmp/paper_extract.json \
  --title "Attention Is All You Need"

{
  "title": "Paper Title (original language)",
  "metadata": {
    "authors": "Author list",
    "year": "2024",
    "venue": "NeurIPS 2024",
    "doi": "10.xxxx/xxxxx",
    "url": "https://arxiv.org/abs/xxxx.xxxxx",
    "source": "arXiv"
  },
  "sections": [
    {
      "heading": "0. Metadata",
      "content": "- Authors: ...\n- Year: ...\n- Venue: ...\n- Code: ..."
    },
    {
      "heading": "1. One-line Summary",
      "content": "What this paper does in one sentence."
    },
    {
      "heading": "2. Problem & Motivation",
      "content": "- What problem does it solve?\n- Why are existing methods insufficient?\n- Why is this research needed?"
    },
    {
      "heading": "3. Key Contributions",
      "content": "1. First contribution\n2. Second contribution\n3. Third contribution"
    },
    {
      "heading": "4. Method",
      "content": "Detailed pipeline/architecture description.\nCore ideas, key equations included.\n\n### Core Idea\n...\n\n### Architecture\n...\n\n### Training\n...\n\n### Key Equations\n$$equation$$"
    },
    {
      "heading": "5. Experiments",
      "content": "### Setup\n- Datasets: ...\n- Baselines: ...\n- Metrics: ...\n\n### Main Results\n- Key numbers and comparisons\n- Where it works and where it doesn't"
    },
    {
      "heading": "6. Ablation & Analysis",
      "content": "- Per-component contributions\n- Interesting analysis results\n- Hyperparameter sensitivity"
    },
    {
      "heading": "7. Limitations & Future Work",
      "content": "- Author-acknowledged limitations\n- Additional limitations you identify\n- Future research directions"
    },
    {
      "heading": "8. Overall Assessment",
      "content": "- Research significance\n- Strengths and weaknesses\n- Connections to related work\n- Ideas applicable to user's research"
    }
  ]
}

python3 scripts/push_to_notion.py \
  /tmp/paper_summary.json \
  --parent-page-id YOUR_PAGE_ID

1. python3 scripts/extract_paper.py -o /tmp/paper_extract.json "https://arxiv.org/abs/..."
2. read /tmp/paper_extract.json (section by section)
3. Write summary → /tmp/paper_summary.json
4. python3 scripts/push_to_notion.py /tmp/paper_summary.json --parent-page-id PAGE_ID