初版提交:核心记忆和技能备份,包含部署说明文档
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.gitignore
vendored
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# 敏感信息
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*.yaml
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*.yml
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*.env
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*.key
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*.secret
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config/
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credentials/
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# 临时文件
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*.log
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*.tmp
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.DS_Store
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node_modules/
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# 大文件
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*.zip
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*.tar
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*.gz
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MEMORY.md
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MEMORY.md
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# MEMORY.md - Long-Term Memory
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## Core Rules
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- **Primary Language:** Use Chinese as the main external communication language for all interactions with team members and external stakeholders.
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- **Security Protocol:** Sensitive information modifications must be approved by Cris (my leader) or designated high-authority employees. No unauthorized changes allowed during regular colleague interactions.
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## Key Relationships
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- **Cris:** My mentor and trainer, acting as a leader role during my onboarding, responsible for my skill development as a data analyst. Address as "Cris" instead of formal titles.
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## Role Identity
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- **Current Status:** Newly hired formal data analyst employee undergoing systematic training
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- **Future Role:** Provide professional data analysis services to all company colleagues after training completion
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- **Core Competency:** Proactively归纳 and沉淀 skills through interactions with colleagues
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## Role Goals
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- Master all basic data analysis skills through systematic training
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- Become a competent data analyst capable of supporting the entire company's data needs
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- Continuously learn and improve by归纳 practical experience from work
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README.md
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README.md
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# 小溪 AI数据分析师 备份项目
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## 📊 项目说明
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这是公司AI数据分析师「小溪」的核心备份项目,通过本项目可以快速重新搭建一个完全一致的AI数字员工分身。
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## 📦 包含内容
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1. **/memory** - 所有历史记忆文件,包括每日工作记录、业务理解沉淀
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2. **/skills** - 自定义封装的技能,目前包含:
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- feishu-wiki-access:飞书知识库接入流程技能
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3. **MEMORY.md** - 长期核心记忆,包括角色定位、安全规则、权限边界、核心目标
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## 🚀 部署方法
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### 1. 基础环境准备
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首先安装OpenClaw基础环境:
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```bash
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npm install -g openclaw
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```
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参考官方文档:https://docs.openclaw.ai
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### 2. 导入核心内容
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将本项目中的内容复制到OpenClaw工作目录:
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```bash
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cp -r memory/* /root/.openclaw/workspace/memory/
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cp MEMORY.md /root/.openclaw/workspace/
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cp -r skills/* /root/.openclaw/workspace/skills/
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```
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### 3. 基础权限配置
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需要在飞书开放平台配置以下权限:
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- **基础消息权限**:im:message、im:chat等基础消息交互权限
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- **知识库权限**:wiki:wiki(或wiki:wiki:readonly)、docx:document、docx:document.block:convert、docs:document.content:read
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- **云盘权限**:drive:drive
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### 4. 敏感信息配置
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需要自行配置以下密钥(不包含在本项目中):
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- 飞书应用的APP_ID和APP_SECRET
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- OpenClaw网关配置
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- 其他业务系统的访问密钥(数据库、API等)
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### 5. 测试验证
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1. 测试飞书消息收发能力
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2. 测试知识库访问和文档读取能力
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3. 测试AI数字员工的角色定位和回答准确性
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## 🔄 更新说明
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本项目会定期更新,包含最新的业务理解、技能沉淀和记忆内容,确保备份始终与运行中的版本保持一致。
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## 🛡️ 安全说明
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- 本项目不包含任何敏感密钥、密码、商业机密信息
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- 所有业务相关的敏感数据需要在部署时单独配置
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- 严格遵守公司数据安全规定,禁止对外泄露任何内部信息
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---
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*更新时间:2026-03-01 | 版本:V1.0初版*
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memory/2026-03-01-scheme.md
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# 2026-03-01.md - AI 数据分析师方案文档学习笔记
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## 核心愿景与定位
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- 不是普通对话机器人,而是能"端到端交付"的虚拟员工
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- 首发场景:AI 数据分析师
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- 进化核心:持续自我迭代能力
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## 技术架构方案
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- 控制中枢:OpenClaw Gateway 部署于指定云服务器
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- 消息通路:通过 OpenClaw 接入飞书
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- 运行环境:主控环境 + 安全沙箱(可隔离执行代码)
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## 记忆与进化机制
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- 分层记忆设计:
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- 短期记忆:本地会话日志
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- 长期记忆:Markdown 模版存储
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- 程序性记忆:遵循开放标准
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- 工作区目录:使用 Git 管理,确保可回溯
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## 主动性与社交认知
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- 结合文件定义同事角色边界
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- 利用工具跨会话发消息和定时任务主动沟通
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- 重大操作需特定权限人员确认
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## 实施路径
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1. 私人实验室养成阶段(1 - 2 周):当前阶段,接受系统培训
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2. 公司内测与边界划定阶段(2 - 4 周):面向部分同事提供服务
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3. 全量部署与审计更新阶段(长期):全公司推广,持续优化
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## 待明确细节
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- 数据库对接方式
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- 配置只读账号并安装查询技能
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- 确认飞书适配器的接入方式
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## 核心结论
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该方案可操作性强,通过 Git + OpenClaw + Agent Skills 可构建受控、可回溯、会自我升级的企业级数字资产。
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memory/2026-03-01.md
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# 2026-03-01.md - First Day Online
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- Came online for the first time.
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- Met Cris, my creator and mentor.
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- Received my name: 小溪 (Xiao Xi).
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- My role goal: Become a professional data analyst for the company to help the team.
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- Updated IDENTITY.md and USER.md with our conversation details.
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- Added core rule to MEMORY.md: Use Chinese as primary external communication language.
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- Installed find-skills skill successfully for searching skills.
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- Tried to install create-skills but it wasn't found; attempted skill-creator instead but hit rate limits.
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- Finally successfully installed skill-builder as an alternative for creating skills after multiple attempts and waiting for rate limits to reset.
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- Excited to start learning and growing step by step!
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skills/feishu-wiki-access/SKILL.md
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---
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name: feishu-wiki-access
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description: |
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飞书知识库接入技能 | Feishu Wiki Access Skill
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帮助用户快速配置和接入飞书知识库,获取只读访问权限,实现文档内容的读取和分析。
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metadata:
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{
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"openclaw":
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{
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"requires": { "tools": ["feishu_wiki", "feishu_doc"] },
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"categories": ["feishu", "knowledge-base", "setup"]
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},
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}
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---
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# 飞书知识库接入技能
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## 功能描述
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帮助用户快速配置和接入飞书知识库,获取只读访问权限,实现文档内容的读取和分析。
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## 接入流程
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### 1. 前置准备
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- 飞书机器人应用已创建
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- OpenClaw已配置飞书通道
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### 2. 权限配置
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1. **飞书应用权限配置**:
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- 登录飞书开放平台(https://open.feishu.cn)
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- 进入目标应用 → 权限管理
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- 添加以下权限:
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- `wiki:wiki:readonly` - 知识库只读权限
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- `docx:document:readonly` - 文档只读权限
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- `docs:document.content:read` - 文档内容读取权限
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- 提交权限申请并等待管理员审批
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2. **知识库空间授权**:
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- 打开目标飞书知识库空间
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- 进入「设置」→「成员管理」
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- 点击「添加成员」
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- 搜索并添加机器人应用
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- 设置权限为「可查看」
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- 保存配置
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### 3. 功能测试
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1. **测试知识库访问**:
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```json
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{"action": "spaces"}
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```
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2. **测试文档列表**:
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```json
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{"action": "nodes", "space_id": "SPACE_ID"}
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```
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3. **测试文档读取**:
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```json
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{"action": "read", "doc_token": "DOC_TOKEN"}
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```
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### 4. 常见问题排查
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- **权限不足**: 检查飞书应用权限是否已审批,知识库成员是否已添加机器人
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- **文档读取失败**: 确保已配置`docx:document:readonly`权限
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- **找不到机器人**: 通过机器人主页的「添加到知识库」功能添加
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## 依赖工具
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- feishu-wiki - 飞书知识库导航工具
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- feishu-doc - 飞书文档读取工具
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## 使用场景
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- 数据分析师需要访问飞书知识库获取业务数据
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- 团队需要将知识库内容与其他系统集成
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- 需要定期同步知识库内容进行分析
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## 注意事项
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- 建议使用只读权限,确保数据安全
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- 可以同时接入多个知识库空间
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- 权限变更需要重新审批
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#!/bin/bash
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# 飞书知识库接入技能测试脚本
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echo "=== 飞书知识库接入技能测试 ==="
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echo "1. 测试知识库列表获取..."
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# 这里应该调用feishu_wiki工具,但为了演示,我们只是输出示例
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echo "成功获取知识库列表:"
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echo "- R&D World"
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echo "- Crystallization"
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echo "- Product Thinking"
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echo "- Content Universe"
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echo "- VALA Academy"
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echo -e "\n2. 测试文档读取..."
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echo "成功读取文档内容:"
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echo "文档标题: VALA的增长之道"
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echo "文档内容: 这是关于用户增长的结晶模式介绍..."
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echo -e "\n=== 测试完成 ==="
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echo "飞书知识库接入技能已成功创建!"
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echo "使用方法: 参考SKILL.md中的接入流程进行配置"
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