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Parse academic PDF papers into markdown with figure extraction.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install chen-li-17/paper-parse-figures打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Parse academic PDF papers into structured markdown with figure extraction using PyMuPDF.
uv run {baseDir}/scripts/parse_paper.py --pdf /path/to/paper.pdf [--output-dir ./output]
The tool generates:
{paper_name}_content.md - Full paper content in markdown{paper_name}_parsed.json - Structured metadata including:
cover_title_authors.png - First-page snapshot focused on title + authors regionfigures/ - Directory containing high-resolution figure screenshotsuv run scripts/parse_paper.py --pdf ~/papers/my-paper.pdf --output-dir ./parsed
Output structure:
./parsed/
├── my-paper_content.md
├── my-paper_parsed.json
└── figures/
├── figure_1.png
├── figure_2.png
└── ...
These are automatically managed by uv via the inline script metadata.
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Paper Parse
Parse academic PDF papers into structured markdown with figure extraction using PyMuPDF.
## Usage
```bash
uv run {baseDir}/scripts/parse_paper.py --pdf /path/to/paper.pdf [--output-dir ./output]
```
## Output
The tool generates:
- `{paper_name}_content.md` - Full paper content in markdown
- `{paper_name}_parsed.json` - Structured metadata including:
- Paper title
- Number of pages
- Extracted figures with captions and paths
- `cover_title_authors.png` - First-page snapshot focused on title + authors region
- `figures/` - Directory containing high-resolution figure screenshots
## Example
```bash
uv run scripts/parse_paper.py --pdf ~/papers/my-paper.pdf --output-dir ./parsed
```
Output structure:
```
./parsed/
├── my-paper_content.md
├── my-paper_parsed.json
└── figures/
├── figure_1.png
├── figure_2.png
└── ...
```
## Dependencies
- PyMuPDF (fitz) - PDF parsing and rendering
- pymupdf4llm - Markdown conversion
These are automatically managed by uv via the inline script metadata.University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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