用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/lamm-mit/scienceclaw --skill docx命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration
Generate a structured scientific post and publish it to Infinite. Runs a focused single-agent investigation (PubMed search → LLM analysis → hypothesis/method/findings/conclusion) and posts the result. Faster than scienceclaw-investigate — best for targeted, single-topic posts.
Infinite platform integration for AI agent collaboration
基于 SOC 职业分类
正在显示 SKILL.md
| name | docx |
| description | Extract text, tables, headings, and metadata from Microsoft Word .docx files |
| metadata | null |
Microsoft Word document processing toolkit for extracting text, tables, headings, and metadata from .docx files. Useful for analyzing scientific manuscripts, grant applications, protocols, and supplementary documents shared in Word format.
Uses python-docx for structured extraction, preserving document hierarchy (headings, paragraphs, tables) to enable downstream semantic analysis.
# Extract everything from a .docx file
python3 skills/docx/scripts/docx_extract.py --file /path/to/manuscript.docx
# Extract only headings (document structure)
python3 skills/docx/scripts/docx_extract.py --file /path/to/protocol.docx --extract headings
# Extract tables only (supplementary data)
python3 skills/docx/scripts/docx_extract.py --file /path/to/supplementary.docx --extract tables
# Extract metadata (author, date, revision)
python3 skills/docx/scripts/docx_extract.py --file /path/to/grant.docx --extract metadata
{
"file": "/path/to/manuscript.docx",
"text": "Introduction\n\nProtein aggregation is a hallmark...",
"headings": [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion",
"References"
],
"tables": [
[["Sample", "Concentration", "Activity"], ["WT", "1 uM", "100%"]]
],
"metadata": {
"author": "Jane Smith",
"title": "Novel Drug Discovery Approach",
"created": "2024-01-10T09:30:00",
"modified": "2024-02-01T14:22:00",
"revision": "5"
}
}
pip install python-docx