Li_doc_answer - 通用文档 AI 答案生成

**版本:** 3.0.4

3,891 stars

Best use case

Li_doc_answer - 通用文档 AI 答案生成 is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

**版本:** 3.0.4

Teams using Li_doc_answer - 通用文档 AI 答案生成 should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/li-doc-answer/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/43622283/li-doc-answer/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/li-doc-answer/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Li_doc_answer - 通用文档 AI 答案生成 Compares

Feature / AgentLi_doc_answer - 通用文档 AI 答案生成Standard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

**版本:** 3.0.4

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Li_doc_answer - 通用文档 AI 答案生成

**版本:** 3.0.4  
**描述:** 通用 Word 文档处理工具,AI 自动识别题目并生成参考答案,支持 doc/docx 格式批量处理  
**作者:** 北京老李

## 功能特性

### v3.0 AI 核心功能
- 🤖 **AI 智能答案生成** - 自动识别文档中的题目并生成参考答案
- 🎯 **8 种题型支持** - 判断/单选/多选/简答/论述/案例/填空/名词解释
- 📝 **自动格式排版** - 统一的答案格式和美观排版
- 🔍 **智能题目识别** - 自动检测文档中的问题

### 基础功能
- ✅ 支持任意 doc/docx 文档处理(不局限于特定主题)
- ✅ 批量文档转换(doc ↔ docx)
- ✅ 文档内容校验与整理
- ✅ Markdown 与 Word 互转
- ✅ 安全无隐私泄露

## 适用场景

- 📚 教育/培训题库文档处理(任意学科)
- 📄 企业办公文档批量转换
- 📝 文档内容整理与归档
- 🔄 格式统一化处理
- 📋 文档答案/备注批量添加

## 使用方法

### AI 答案生成(v3.0 核心功能)

```bash
# AI 自动识别题目并生成答案
python3 scripts/ai_generate_answers.py <输入文件> [输出文件]

# 示例
python3 scripts/ai_generate_answers.py 题库.doc
# 输出:题库_AI 答案版.docx
```

### 其他功能

```bash
# 处理单个文档
python3 scripts/generate_answers.py <输入文件> [输出文件]

# 批量处理目录
python3 scripts/generate_all_answers.py <目录路径>

# 格式转换
python3 scripts/convert_md_to_docx.py <输入.md> <输出.docx>

# 文档校验
python3 scripts/check_answers.py <文件路径>
```

## 支持题型

| 题型 | AI 识别 | 答案格式 |
|------|--------|----------|
| 判断题 | ✅ | 正确/错误 + 理由 |
| 单选题 | ✅ | 正确选项 + 解析 |
| 多选题 | ✅ | 正确选项 + 解析 |
| 简答题 | ✅ | 要点 1/2/3 + 详细说明 |
| 论述题 | ✅ | 引言 + 主体论述 + 结论 |
| 案例分析 | ✅ | 问题识别 + 理论应用 + 解决方案 + 总结 |
| 填空题 | ✅ | 正确答案 |
| 名词解释 | ✅ | 定义 + 特点 + 意义 |

## 文件结构

```
Li_doc_answer/
├── SKILL.md              # 技能说明
├── README.md             # 使用文档(中文)
├── README_EN.md          # 使用文档(英文)
├── data/                 # 待处理文件目录(可选)
└── scripts/
    ├── ai_generate_answers.py    # AI 答案生成(核心)
    ├── generate_answers.py       # 单文档处理
    ├── generate_all_answers.py   # 批量处理
    ├── complete_all_answers.py   # 完整处理
    ├── add_answers_to_questions.py # 答案添加
    ├── check_answers.py          # 文档校验
    └── convert_md_to_docx.py     # 格式转换
```

## 安全说明

- ✅ 无 API 密钥硬编码
- ✅ 无个人隐私数据
- ✅ 无外部网络请求
- ✅ 仅本地文件操作
- ✅ 使用相对路径,可跨环境部署

## 依赖

```bash
pip3 install python-docx mammoth
```

## 更新日志

- v3.0.1 - AI 答案生成核心版本,支持 8 种题型自动识别和答案生成
- v3.0.0 - 新增 AI 智能答案生成,自动识别题目并生成参考答案
- v2.0.0 - 升级为通用文档处理工具,支持任意 doc/docx 文档
- v1.0.0 - 初始版本

## 核心功能

### v3.0 新增
- ✅ **AI 智能答案生成** - 自动为题目生成参考答案
- ✅ **自动问题识别** - 智能识别文档中的题目
- ✅ **多题型支持** - 判断、单选、多选、简答、论述、案例、填空、名词解释
- ✅ **答案格式化** - 统一的答案格式和排版

### v2.0 功能
- ✅ 通用文档处理
- ✅ 批量处理
- ✅ 格式转换
- ✅ 文档校验

Related Skills

answers

3891
from openclaw/skills

USE FOR AI-grounded answers via OpenAI-compatible /chat/completions. Two modes: single-search (fast) or deep research (enable_research=true, thorough multi-search). Streaming/blocking. Citations.

Data & Research

answer-framework

3891
from openclaw/skills

智能回答框架,自动适配问题类型,提供有据可依的自然回答。 / Smart answering framework that adapts to question types and delivers evidence-based, natural responses.

reasoning-answer

3891
from openclaw/skills

Current Date: $DATE$. Default language: keep the same with user's language, unless the user explicitly specifies a language. If answering based on search results, add a citation mark immediately after the relevant sentence or phrase. 2. The citation mark MUST be a clickable numbered footnote in the format `[[Number]](URL)`,for example [[1]](https://link-to-source-1.com). At the end, there shoul...

knowledge-answer

3891
from openclaw/skills

Current Date: $DATE$. Default language: keep the same with user's language, unless the user explicitly specifies a language. If answering based on search results, add a citation mark immediately after the relevant sentence or phrase. 2. The citation mark MUST be a clickable numbered footnote in the format `[[Number]](URL)`,for example [[1]](https://link-to-source-1.com). At the end, there shoul...

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning