Word Parser

👤 veeicwgy 📦 v0.2.0 ⭐ 4.1 ⬇️ 679 下載
📄 辦公效率 免費

📖 技能介紹


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文件解析', '提取Word結構', '分析Word檔案內容', '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/

  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

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  • Use extract when user needs tables, formulas, or structured JSON
  • .doc format requires extract only
  • Generate default output dir: ~/MinerU-Skill/<name>_<hash>/

🤖 AI 評測

這是一個實用的 Word 文件解析工具,能快速提取文件結構、表格和圖片。質量中等偏上,文件清晰但內容偏少。優點是使用簡單、支援多種解析模式;不足是缺少使用示例,複雜場景的指導不足。對於基礎文件解析需求足夠使用,但深度應用可能需要更多參考文件。版本較新,可能存在最佳化空間。

📊 多維度評分

適應性4.3
規範性3.9
有效性4.3
可靠性3.8
可信度4.8

📁 包含檔案 (2 個)

📄 SKILL.md 2 KB
📄 _meta.json 130 B