据 AlphaMoat 统计,截至 2026-09,pdf-parser-mineru 累计下载 3,034 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 3,708 位,在「办公效率」分类(435 个)中排名第 272 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 79 | 2,608 | - | - |
| SkillHub ↗ | 260 | 3,034 | 1 | — |
各平台的计数口径不同,统计时间不一致。
提供 pdf_to_markdown 和 pdf_to_json 两种工具,可保留文档结构、公式、表格和图片。可选 hybrid-auto-engine、pipeline 或 vlm-auto-engine 后端;OCR 支持多种语言。本地安装需要较新的 Python、充足内存和磁盘空间,部分后端需要 NVIDIA GPU 或 Apple Silicon。所有路径必须使用绝对路径,页码从零开始。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,034 | — | 1 |
| 2026-08 | 2,663 | +8.8% | 1 |
| 2026-07 | 2,447 | +12.0% | 1 |
| 2026-06 | 2,185 | +9.2% | 1 |
| 2026-05 | 2,001 | — | - |
| 2026-03 | 1,527 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: pdf-process-mineru description: PDF document parsing tool based on local MinerU, supports converting PDF to Markdown, JSON, and other machine-readable formats. --- ## Tool List ### 1. pdf_to_markdown Convert PDF documents to Markdown format, preserving document structure, formulas, tables, and images.
**Description**: Use MinerU to parse PDF documents and output in Markdown format, supporting OCR, formula recognition, table extraction, and other features.
**Parameters**:
- `file_path` (string, required): Absolute path to the PDF file
- `output_dir` (string, required): Absolute path to the output directory
- `backend` (string, optional): Parsing backend, options: `hybrid-auto-engine` (default), `pipeline`, `vlm-auto-engine`
- `language` (string, optional): OCR language code, such as `en` (English), `ch` (Chinese), `ja` (Japanese), etc., defaults to auto-detection
- `enable_formula` (boolean, optional): Whether to enable formula recognition, defaults to true
- `enable_table` (boolean, optional): Whether to enable table extraction, defaults to true
- `start_page` (integer, optional): Start page number (starting from 0), defaults to 0
- `end_page` (integer, optional): End page number (starting from 0), defaults to -1 meaning parse all pages
**Return Value**:
```json
{
"success": true,
"output_path": "/path/to/output",
"markdown_content": "Converted Markdown content...",
"images": ["List of image paths"],
"tables": ["List of table information"],
"formula_count": 10
}
```
**Examples**:
```bash
python .claude/skills/pdf-process/script/pdf_parser.py \
'{"name": "pdf_to_markdown", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output"}}'
# Use specific backend
python .claude/skills/pdf-process/script/pdf_parser.py \
'{"name": "pdf_to_markdown", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output", "backend": "pipeline"}}'
# Parse specific pages
python .claude/skills/pdf-process/script/pdf_parser.py \
'{"name": "pdf_to_markdown", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output", "start_page": 0, "end_page": 5}}'
```
---
### 2. pdf_to_json
Convert PDF documents to JSON format, including detailed layout and structural information.
**Description**: Use MinerU to parse PDF documents and output in JSON format, containing structured information such as text blocks, images, tables, formulas, etc.
**Parameters**:
- `file_path` (string, required): Absolute path to the PDF file
- `output_dir` (string, required): Absolute path to the output directory
- `backend` (string, optional): Parsing backend, options: `hybrid-auto-engine` (default), `pipeline`, `vlm-auto-engine`
- `language` (string, optional): OCR language code, such as `en` (English), `ch` (Chinese), `ja` (Japanese), etc., defaults to auto-detection
- `enable_formula` (boolean, optional): Whether to enable formula recognition, defaults to true
- `enable_table` (boolean, optional): Whether to enable table extraction, defaults to true
- `start_page` (integer, optional): Start page number (starting from 0), defaults to 0
- `end_page` (integer, optional): End page number (starting from 0), defaults to -1 meaning parse all pages
**Return Value**:
```json
{
"success": true,
"output_path": "/path/to/output.json",
"pages": [
{
"page_no": 0,
"page_size": [595, 842],
"blocks": [
{
"type": "text",
"text": "Text content",
"bbox": [x, y, x, y]
}
],
"images": [],
"tables": [],
"formulas": []
}
],
"metadata": {
"total_pages": 10,
"author": "Author",
"title": "Title"
}
}
```
**Examples**:
```bash
python .claude/skills/pdf-process/script/pdf_parser.py \
'{"name": "pdf_to_json", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output"}}'
# Use specific backend and language
python .claude/skills/pdf-process/script/pdf_parser.py \
'{"name": "pdf_to_json", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output", "backend": "hybrid-auto-engine", "language": "ch"}}'
```
---
## Installation Instructions
### 1. Install MinerU
```bash
# Update pip and install uv
pip install --upgrade pip
pip install uv
# Install MinerU (including all features)
uv pip install -U "mineru[all]"
```
### 2. Verify Installation
```bash
# Check if MinerU is installed successfully
mineru --version
# Test basic functionality
mineru --help
```
### 3. System Requirements
- **Python Version**: 3.10-3.13
- **Operating System**: Linux / Windows / macOS 14.0+
- **Memory**:
- Using `pipeline` backend: minimum 16GB, recommended 32GB+
- Using `hybrid/vlm` backend: minimum 16GB, recommended 32GB+
- **Disk Space**: minimum 20GB (SSD recommended)
- **GPU** (optional):
- `pipeline` backend: supports CPU-only
- `hybrid/vlm` backend: requires NVIDIA GPU (Volta architecture and above) or Apple Silicon
## Use Cases
1. **Academic Paper Parsing**: Extract structured content such as formulas, tables, and images
2. **Technical Document Conversion**: Convert PDF documents to Markdown for version control and online publishing
3. **OCR Processing**: Process scanned PDFs and garbled PDFs
4. **Multilingual Documents**: Supports OCR recognition for 109 languages
5. **Batch Processing**: Batch convert multiple PDF documents
## Backend Selection Recommendations
- **hybrid-auto-engine** (default): Balanced accuracy and speed, suitable for most scenarios
- **pipeline**: Suitable for CPU-only environments, best compatibility
- **vlm-auto-engine**: Highest accuracy, requires GPU acceleration
## Notes
1. **File Paths**: All paths must be absolute paths
2. **Output Directory**: Non-existent directories will be created automatically
3. **Performance**: Using GPU can significantly improve parsing speed
4. **Page Numbers**: Page numbers start counting from 0
5. **Memory**: Processing large documents may consume more memory
## Troubleshooting
### Common Issues
1. **Installation Failure**:
- Ensure using Python 3.10-3.13
- Windows only supports Python 3.10-3.12 (ray does not support 3.13)
- Using `uv pip install` can resolve most dependency conflicts
2. **Insufficient Memory**:
- Use `pipeline` backend
- Limit parsing pages: `start_page` and `end_page`
- Reduce virtual memory allocation
3. **Slow Parsing Speed**:
- Enable GPU acceleration
- Use `hybrid-auto-engine` backend
- Disable unnecessary features (formulas, tables)
4. **Low OCR Accuracy**:
- Specify the correct document language
- Ensure the backend supports OCR (use `pipeline` or `hybrid-*`)
## Related Resources
- MinerU Official Documentation: https://opendatalab.github.io/MinerU/
- MinerU GitHub: https://github.com/opendatalab/MinerU
- Online Demo: https://mineru.net/
通过 MCP 在腾讯文档里新建、编辑与管理在线文档的完整操作手册。
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通过命令行访问 Gmail、日历、Drive、通讯录、Sheets 与 Docs。
PDF和图片文字提取 将文档文字、表格与扫描页识别整理为文本结果。
按主题与风格自动生成 PPT 文件的技能。
通过 kdocs-cli 操作金山文档云文档的官方技能。
用自然语言指令改 PDF 指定页的小工具。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。