據 AlphaMoat 統計,截至 2026-09,pdf-parser-mineru 累計下載 3,034 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,708 位,在「辦公效率」分類(435 個)中排名第 272 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 79 | 2608 | - | - |
| SkillHub ↗ | 260 | 3034 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
提供 pdf_to_markdown 和 pdf_to_json 兩種工具,可保留文件結構、公式、表格和圖片。可選 hybrid-auto-engine、pipeline 或 vlm-auto-engine 後端;OCR 支援多種語言。本地安裝需要較新的 Python、充足記憶體和磁碟空間,部分後端需要 NVIDIA GPU 或 Apple Silicon。所有路徑必須使用絕對路徑,頁碼從零開始。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3034 | — | 1 |
| 2026-08 | 2663 | +8.8% | 1 |
| 2026-07 | 2447 | +12.0% | 1 |
| 2026-06 | 2185 | +9.2% | 1 |
| 2026-05 | 2001 | — | - |
| 2026-03 | 1527 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 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/
透過 MCP 在騰訊文件裡新建、編輯與管理線上文件的完整操作手冊。
在保留公式、格式和活頁簿結構的前提下建立、檢查或編輯 Excel 檔案。
處理 Word 與 DOCX 文件的作業指南,著重維持樣式、編號與版面。
透過命令列存取 Gmail、日曆、Drive、Contacts、Sheets 與 Docs。
PDF和圖片文字提取 將文件文字、表格與掃描頁識別整理為文字結果。
按主題與風格自動生成 PPT 檔案的技能。
透過 kdocs-cli 操作金山文件雲文件的官方技能。
用自然語言指令改 PDF 指定頁的小工具。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。