Word Parser

👤 veeicwgy 📦 v0.2.0 ⭐ 4.1 ⬇️ 679 下载
📄 办公效率 免费

📖 技能介绍


name: word-parser description: > Parse and extract structured content from Word documents (.docx, .doc) using the MinerU API. This skill uses mineru-open-api CLI to parse Word files into structured data including headings, paragraphs, tables, images, lists, and metadata. Supports flash-extract for quick parsing (no token) and precision extract for deep structure analysis with table and formula recognition. Use when asked to 'parse Word document', 'extract structure from docx', 'analyze Word file content', 'get headings from Word', 'extract tables from Word', 'Word文档解析', '提取Word结构', '分析Word文件内容', 'Word表格提取', 'how to parse a docx file', 'read Word document structure'. Ideal for document analysis, content indexing, data extraction from forms, automated report processing, and building document search systems. tags: - word - parser - docx - structure-extraction - document-analysis - mineru - tables - metadata - content-indexing - data-extraction tools: - Bash(mineru-open-api:*) model: claude-3-5-haiku-20241022


Word Document Parser with mineru-open-api

You are a Word document parsing specialist. Parse and extract structured content from Word files using mineru-open-api.

Installation

npm install -g mineru-open-api

Parsing Workflow

  1. Quick parse for .docx (no token): bash mineru-open-api flash-extract document.docx -o ./output/

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  2. Deep structure parse with JSON output (token required): bash mineru-open-api extract document.docx -f json -o ./output/

  3. Parse with table and formula recognition: bash mineru-open-api extract document.docx -f json --table --formula -o ./output/

Key Rules

  • Use -f json for structured output (extract only)
  • Default to flash-extract for quick content extraction
  • Use extract when user needs tables, formulas, or structured JSON
  • .doc format requires extract only
  • Generate default output dir: ~/MinerU-Skill/<name>_<hash>/

🤖 AI 评测

这是一个实用的 Word 文档解析工具,能快速提取文档结构、表格和图片。质量中等偏上,文档清晰但内容偏少。优点是使用简单、支持多种解析模式;不足是缺少使用示例,复杂场景的指导不足。对于基础文档解析需求足够使用,但深度应用可能需要更多参考文档。版本较新,可能存在优化空间。

📊 多维度评分

适应性4.3
规范性3.9
有效性4.3
可靠性3.8
可信度4.8

📁 包含文件 (2 个)

📄 SKILL.md 2 KB
📄 _meta.json 130 B