No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
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🔒 Is feishu-lark-agent safe to install? View the security audit →
feishu-lark-agent 中文 | English 中文文档 让 Claude Code 直接操控飞书——发消息、建文档、管日程、写多维表格,全部用自然语言完成。 零依赖 Python 脚本,调用飞书开放 API,配合 Claude Code 使用效果最佳。 安装 自然语言对话示例 安装并配置完成后,直接和 Claude Code 说话就好,不需要记任何命令。 💬 发消息 「发飞书消息给 zhang@company.com,说今天的站会改到11点」 Claude 自动通过邮箱查到 openid,发送消息,返回确认。 「给乔木龙虾俱乐部群发一条消息:周五下午茶,大家来玩」 Claude 先列出群聊找到 chatid,再发送到群组。 📄 文档 「帮我创建一个飞书文档,标题「2026 Q2 OKR」,内容从这个文件读:/tmp/okr.md」 Claude 创建文档,写入内容,自动将你加为编辑者,返回文档链接。 「读一下这个飞书文档的内容:https://xxx.feishu.cn/docx/DOCID」 Claude 提取 URL 中的 documentid,调用接口返回全文。 📅 日历 「明天下午3点到4点,帮我创建一个「产品评审会」日程,地点3楼大会议室」 Claude 解析时间、创建日程,并自动发送日历邀请给你(需配置 )。 「帮我看看本周还有哪些日程」 Claude 查询未来7天的日历事件,整理后展示给你。 📊 多维表格 「在我的读书记录表格里加一条:《穷查理宝典》,查理·芒格,状态在读」 (表格链接:https://xxx.feishu.cn/base/APPTOKEN) Claude 先查表格字段结构,再按字段名写入记录。 「把多维表格里所有状态为「待审核」的记录都列出来」 Claude 用 Feishu 过滤语法查询并展示结果。 ✅ 任务 「帮我创建一个飞书任务:准备季度述职,截止日期3月25日,备注要准备PPT和数据」 Claude 调用 Task API 创建任务并返回任务 ID。 🔍 复合场景 「查一下公司有没有叫王芳的同事,找到了就给她发一条飞书消息,说明天的设计评审希望她参加」 Claude 先用 找人,确认后再发消息,两步自动完成。 「帮我把 /tmp/meetingnotes.md 的内容创建成飞书文档,然后发消息给 product-team@company.com 告诉他们文档链接」 Claude 创建文档拿到 URL,再发消息附上链接,一气呵成。 第一步:创建飞书自建应用,获取 App ID 和 App Secret 这是唯一需要手动操作的步骤,约 5 分钟完成。 1. 进入飞书开发者后台 打开 [https://open.feishu.cn/app](https://open.feishu.cn/
| Stars | 52 |
| Forks | 4 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 65.5173024616068/100 |
| Open Issues | 1 |
| Last Updated | 2026-03-22 |
| Created | 2026-03-12 |
| Platforms | python |
| Est. Tokens | ~6k |
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feishu-lark-agent is Comprehensive Feishu/Lark workspace agent. Handles messages, docs, bitable (multi-dimensional tables), calendar, and tasks via Feishu Open API.. It is categorized as a AI Tool with 52 GitHub stars.
feishu-lark-agent is primarily written in Python.
You can find installation instructions and usage details in the feishu-lark-agent GitHub repository at github.com/joeseesun/feishu-lark-agent. The project has 52 stars and 4 forks, indicating an active community.
feishu-lark-agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to feishu-lark-agent on Agent Skills Hub include claude-code-voice-skill, maui-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: