Agent skill

Feishu Automation

by aAAaqwq in aAAaqwq/AGI-Super-Team

飞书(Lark)全通道自动化。使用 lark-mcp 工具操作飞书多维表格(Bitable)、发送消息、管理文档、创建群组、自动化工作流等。当用户需要操作飞书平台、同步数据到飞书表格、发送飞书通知、管理飞书文档或自动化飞书业务流程时使用此技能。

MITAuto-check: notesProductivity & Automation

Install Feishu Automation

skills CLI
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/feishu-automation .claude/skills/feishu-automation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
feishu-automation
GitHub stars
105
Used in
1 other repo
Token cost
~2.3k tokens
SKILL.md length
321 words
Files
8 (incl. scripts)
Skills in repo
167
Repo updated
First seen
Licence
MIT

At a glance

飞书(Lark)全通道自动化。使用 lark-mcp 工具操作飞书多维表格(Bitable)、发送消息、管理文档、创建群组、自动化工作流等。当用户需要操作飞书平台、同步数据到飞书表格、发送飞书通知、管理飞书文档或自动化飞书业务流程时使用此技能。

  • Works in 11 steps: 多维表格(Bitable) → 消息发送 → 文档管理 → …
  • Tasks that involve Messaging and chat bots
  • SKILL.md covers 核心功能, 快速开始, 工作流程 and API 工具参考, plus 2 more sections
  • Runs Python, Shell and JavaScript scripts from its folder; calls curl and python3; reaches open.feishu.cn and xxx.feishu.cn; needs FILE_TOKEN and DOC_TOKEN

What it does

Feishu Automation is an agent skill from aAAaqwq/AGI-Super-Team. 飞书(Lark)全通道自动化。使用 lark-mcp 工具操作飞书多维表格(Bitable)、发送消息、管理文档、创建群组、自动化工作流等。当用户需要操作飞书平台、同步数据到飞书表格、发送飞书通知、管理飞书文档或自动化飞书业务流程时使用此技能。

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts (for example `bitable.py`, `card_builder.py` and `feishu-mcp-setup.js`).

It sits in Productivity & Automation, covering Messaging and chat bots. It works with Model Context Protocol and Feishu (Lark). The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.

When your agent uses it

  • Tasks that involve Messaging and chat bots

Example prompts

  • “/feishu-automation”

Requirements

  • Python 3
  • Node.js
  • A Bash shell
  • A credential in YOUR_APP_SECRET
  • A credential in FILE_TOKEN
  • Pre-approved tools (allowed-tools): mcp__lark-mcp_*, Bash, Read, Write, Edit

Workflow steps

11 steps, taken from the step headings in SKILL.md.

  1. 多维表格(Bitable)
  2. 消息发送
  3. 文档管理
  4. 群组管理
  5. 知识库(Wiki)
  6. 日历和任务
  7. 自动化日报收集
  8. 审批流程
  9. 任务管理
  10. 客户管理
  11. 报表生成

What it can do on your machine

Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • mcp__lark-mcp_*
    • Bash
    • Read
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python, Shell and JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • curl
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • open.feishu.cn
    • xxx.feishu.cn

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • FILE_TOKEN
    • DOC_TOKEN
    • APP_SECRET

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Feishu Automation loads about 2.3k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 321 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: mcp__lark-mcp_*, Bash, Read, Write, Edit

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 321 words, ~2,261 tokens.

Download SKILL.mdSave it as .claude/skills/feishu-automation/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
feishu-automation
description
飞书(Lark)全通道自动化。使用 lark-mcp 工具操作飞书多维表格(Bitable)、发送消息、管理文档、创建群组、自动化工作流等。当用户需要操作飞书平台、同步数据到飞书表格、发送飞书通知、管理飞书文档或自动化飞书业务流程时使用此技能。
allowed-tools
mcp__lark-mcp_*, Bash, Read, Write, Edit

飞书全通道自动化

使用 lark-mcp 工具实现飞书平台的全面自动化操作。

核心功能

1. 多维表格(Bitable)
  • 创建多维表格和数据表
  • 添加、修改、删除字段
  • 增删改查记录数据
  • 批量导入导出数据
  • 数据筛选和排序
2. 消息发送
  • 发送文本、富文本、卡片消息
  • 群组消息和私聊消息
  • 消息模板和交互式卡片
  • 文件和图片发送
3. 文档管理
  • 搜索云文档
  • 创建新文档
  • 编辑文档内容
  • 文档权限管理
  • 文档协作者管理
4. 群组管理
  • 创建群组
  • 添加/移除成员
  • 获取群组列表
  • 群组信息查询
5. 知识库(Wiki)
  • 搜索知识库节点
  • 获取节点详情
  • 创建和管理知识库内容
6. 日历和任务
  • 创建和查询日历事件
  • 创建和管理任务
  • 任务分配和跟踪

快速开始

检查 MCP 可用性
javascript
// 检查 lark-mcp 工具是否可用
// 可用工具前缀:mcp__lark-mcp_
发送测试消息
javascript
// 发送文本消息到群组
await mcp__lark-mcp_sendMessage({
  receive_id: "oc_xxxxxxxxx",
  msg_type: "text",
  content: JSON.stringify({
    text: "Hello from Clawdbot!"
  })
});

工作流程

数据同步流程
  1. 连接数据源
  2. 转换数据格式
  3. 创建/更新多维表格
  4. 批量写入数据
  5. 发送通知
消息推送流程
  1. 触发事件(定时/事件驱动)
  2. 构建消息内容
  3. 获取接收者 ID
  4. 发送消息
  5. 记录日志
文档自动化流程
  1. 获取文档模板
  2. 填充内容
  3. 创建新文档
  4. 设置权限
  5. 分享给团队

API 工具参考

多维表格相关
  • createBitable - 创建多维表格
  • createTable - 创建数据表
  • addRecord - 添加记录
  • updateRecord - 更新记录
  • deleteRecord - 删除记录
  • searchRecords - 搜索记录
  • getRecord - 获取记录详情
消息相关
  • sendMessage - 发送消息
  • getMessages - 获取消息历史
  • replyMessage - 回复消息
文档相关
  • searchDocs - 搜索文档
  • createDoc - 创建文档
  • getDoc - 获取文档内容
  • updateDoc - 更新文档
  • setDocPermission - 设置文档权限
📄 Markdown 导入云文档(推荐方式)

最佳实践:将本地 Markdown 文件直接导入为飞书云文档,格式完整保留。

bash
# 1. 获取 access_token
TOKEN=$(curl -s -X POST 'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal' \
  -H 'Content-Type: application/json' \
  -d '{"app_id":"YOUR_APP_ID","app_secret":"YOUR_APP_SECRET"}' \
  | python3 -c "import sys,json; print(json.load(sys.stdin).get('tenant_access_token',''))")

# 2. 上传 md 文件到飞书云盘
FILE_TOKEN=$(curl -s -X POST 'https://open.feishu.cn/open-apis/drive/v1/files/upload_all' \
  -H "Authorization: Bearer $TOKEN" \
  -F "file_name=document.md" \
  -F "parent_type=explorer" \
  -F "parent_node=" \
  -F "size=$(stat -c%s /path/to/document.md)" \
  -F "file=@/path/to/document.md" \
  | python3 -c "import sys,json; print(json.load(sys.stdin).get('data',{}).get('file_token',''))")

# 3. 导入为飞书云文档
TICKET=$(curl -s -X POST 'https://open.feishu.cn/open-apis/drive/v1/import_tasks' \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "file_extension": "md",
    "file_token": "'"$FILE_TOKEN"'",
    "type": "docx",
    "point": {"mount_type": 1, "mount_key": ""}
  }' | python3 -c "import sys,json; print(json.load(sys.stdin).get('data',{}).get('ticket',''))")

# 4. 等待导入完成,获取文档链接
sleep 2
curl -s -X GET "https://open.feishu.cn/open-apis/drive/v1/import_tasks/$TICKET" \
  -H "Authorization: Bearer $TOKEN" \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d.get('data',{}).get('result',{}).get('url',''))"

支持的导入格式:

  • md → Markdown
  • docx → Word 文档
  • xlsx → Excel 表格

注意事项:

  • 导入是异步操作,需要轮询 import_tasks/{ticket} 获取结果
  • mount_type: 1 表示导入到"我的空间"
  • 导入后的文档 URL 格式:https://xxx.feishu.cn/docx/{token}
📤 完整输出云文档流程(标准操作)

每次输出云文档时,必须完成以下步骤:

  1. 生成本地 Markdown 文件
  2. 上传到飞书云盘 → drive/v1/files/upload_all
  3. 导入为云文档 → drive/v1/import_tasks
  4. 设置权限为组织内可编辑 → drive/v1/permissions/{token}/public
  5. 发送链接到目标群
bash
# 完整流程脚本
TOKEN=$(curl -s -X POST 'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal' \
  -H 'Content-Type: application/json' \
  -d '{"app_id":"APP_ID","app_secret":"APP_SECRET"}' \
  | python3 -c "import sys,json; print(json.load(sys.stdin).get('tenant_access_token',''))")

# 1. 上传文件
FILE_TOKEN=$(curl -s -X POST 'https://open.feishu.cn/open-apis/drive/v1/files/upload_all' \
  -H "Authorization: Bearer $TOKEN" \
  -F "file_name=document.md" \
  -F "parent_type=explorer" \
  -F "parent_node=" \
  -F "size=$(stat -c%s document.md)" \
  -F "file=@document.md" \
  | python3 -c "import sys,json; print(json.load(sys.stdin).get('data',{}).get('file_token',''))")

# 2. 导入为云文档
TICKET=$(curl -s -X POST 'https://open.feishu.cn/open-apis/drive/v1/import_tasks' \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"file_extension":"md","file_token":"'"$FILE_TOKEN"'","type":"docx","point":{"mount_type":1,"mount_key":""}}' \
  | python3 -c "import sys,json; print(json.load(sys.stdin).get('data',{}).get('ticket',''))")

sleep 2

# 3. 获取文档 token
DOC_RESULT=$(curl -s -X GET "https://open.feishu.cn/open-apis/drive/v1/import_tasks/$TICKET" \
  -H "Authorization: Bearer $TOKEN")
DOC_TOKEN=$(echo "$DOC_RESULT" | python3 -c "import sys,json; print(json.load(sys.stdin).get('data',{}).get('result',{}).get('token',''))")
DOC_URL=$(echo "$DOC_RESULT" | python3 -c "import sys,json; print(json.load(sys.stdin).get('data',{}).get('result',{}).get('url',''))")

# 4. 设置权限:组织内可编辑
curl -s -X PATCH "https://open.feishu.cn/open-apis/drive/v1/permissions/$DOC_TOKEN/public?type=docx" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"external_access_entity":"open","security_entity":"anyone_can_view","comment_entity":"anyone_can_view","share_entity":"anyone","link_share_entity":"tenant_editable"}'

# 5. 发送到群
curl -s -X POST "https://open.feishu.cn/open-apis/im/v1/messages?receive_id_type=chat_id" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"receive_id":"CHAT_ID","msg_type":"text","content":"{\"text\":\"📄 文档已上传:\\n\\n'"$DOC_URL"'\"}"}'

权限设置说明:

  • link_share_entity: "tenant_editable" → 组织内获得链接的人可编辑
  • comment_entity: "anyone_can_view" → 任何人可评论
  • share_entity: "anyone" → 任何人可分享
群组相关
  • createGroup - 创建群组
  • addMember - 添加成员
  • getGroupList - 获取群组列表
  • getGroupInfo - 获取群组信息

实用场景

1. 自动化日报收集
  • 每日定时创建表格记录
  • 成员填写日报
  • 自动汇总统计
  • 发送到群组
2. 审批流程
  • 创建审批表格
  • 监听状态变更
  • 自动通知审批人
  • 记录审批历史
3. 任务管理
  • 创建任务表格
  • 分配任务给成员
  • 发送任务提醒
  • 跟踪完成状态
4. 客户管理
  • 客户信息表格
  • 跟进记录
  • 自动提醒
  • 数据可视化
5. 报表生成
  • 从表格提取数据
  • 生成统计报表
  • 创建飞书文档
  • 定期推送更新

最佳实践

认证配置
  • 使用提供的 App ID 和 App Secret
  • 遵守 API 调用频率限制
  • 缓存 access_token
数据操作
  • 批量操作使用分页
  • 数据写入前验证格式
  • 错误处理和重试
  • 记录操作日志
消息发送
  • 使用交互式卡片提升体验
  • 合理控制发送频率
  • 避免发送敏感信息
  • 支持用户交互
权限管理
  • 最小权限原则
  • 定期审查权限
  • 协作者生命周期管理

错误处理

常见错误
  • 权限不足 - 检查应用权限配置
  • 限流错误 - 实现重试和等待
  • 无效 ID - 验证用户/群组 ID 格式
  • 网络错误 - 实现重试机制
重试策略
  • 指数退避算法
  • 最大重试次数限制
  • 记录失败请求
  • 通知管理员

安全注意事项

  • 保护 App Secret
  • 不要在日志中记录敏感信息
  • 使用环境变量管理凭证
  • 定期轮换访问令牌
  • 遵守数据隐私法规

示例代码

创建多维表格并添加数据
javascript
// 创建多维表格
const bitable = await mcp__lark-mcp_createBitable({
  name: "项目管理",
  folder_token: "folder_token"
});

// 创建数据表
const table = await mcp__lark-mcp_createTable({
  app_token: bitable.app_token,
  table: {
    name: "任务列表",
    fields: [
      { field_name: "任务名称", type: 1 },
      { field_name: "负责人", type: 13 },
      { field_name: "状态", type: 3 },
      { field_name: "截止日期", type: 5 }
    ]
  }
});

// 添加记录
await mcp__lark-mcp_addRecord({
  app_token: bitable.app_token,
  table_id: table.table_id,
  fields: {
    "任务名称": "完成项目文档",
    "负责人": "user_id",
    "状态": "进行中",
    "截止日期": Date.now()
  }
});
发送卡片消息
javascript
await mcp__lark-mcp_sendMessage({
  receive_id: "chat_id",
  msg_type: "interactive",
  content: JSON.stringify({
    config: {
      wide_screen_mode: true
    },
    header: {
      template: "turquoise",
      title: {
        content: "重要通知",
        tag: "plain_text"
      }
    },
    elements: [
      {
        tag: "div",
        text: {
          content: "**项目里程碑已完成**",
          tag: "lark_md"
        }
      },
      {
        tag: "action",
        actions: [
          {
            tag: "button",
            text: {
              content: "查看详情",
              tag: "plain_text"
            },
            type: "primary",
            url: "https://example.com"
          }
        ]
      }
    ]
  })
});
批量导入数据
javascript
const data = [
  { name: "张三", phone: "13800138000" },
  { name: "李四", phone: "13900139000" }
];

for (const item of data) {
  await mcp__lark-mcp_addRecord({
    app_token: "app_token",
    table_id: "table_id",
    fields: {
      "姓名": item.name,
      "电话": item.phone
    }
  });

  // 避免限流
  await new Promise(resolve => setTimeout(resolve, 100));
}

配置验证

检查 MCP 服务器
bash
# 检查 .claude.json 中的 lark-mcp 配置
cat ~/.claude.json | grep -A 15 "lark-mcp"
测试连接
javascript
// 发送测试消息验证连接
await mcp__lark-mcp_sendMessage({
  receive_id: "your_chat_id",
  msg_type: "text",
  content: JSON.stringify({
    text: "🎉 飞书 MCP 连接成功!"
  })
});

进阶用法

Webhook 集成
  • 监听飞书 Webhook 事件
  • 自动触发工作流
  • 实时数据同步
自动化定时任务
  • 定时发送报告
  • 自动数据备份
  • 定期清理
跨平台集成
  • 与 GitHub 集成(Issue 同步)
  • 与邮件集成(通知推送)
  • 与日历集成(日程管理)

故障排查

MCP 工具不可用
  1. 重启 Claude Desktop
  2. 检查网络连接
  3. 验证凭证是否有效
  4. 查看错误日志
API 调用失败
  1. 检查应用权限配置
  2. 验证用户/群组 ID
  3. 查看限流状态
  4. 检查数据格式
权限不足
  1. 登录飞书开放平台
  2. 检查应用权限范围
  3. 重新授权
  4. 等待权限生效

© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts) in skills/feishu-automation of aAAaqwq/AGI-Super-Team.

  • SKILL.md
  • bitable.py
  • card_builder.py
  • feishu-mcp-setup.js
  • feishu-mcp-setup.sh
  • feishu-send.sh
  • feishu_api.py
  • scripts/md2feishu.sh

Open the folder on GitHubat commit 7cefd81

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in aAAaqwq/AGI-Super-Team, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Feishu Automation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Feishu Automation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Feishu Automation this skillaAAaqwq/AGI-Super-Team1051 repos~2.3kAutomated safety check: NotesMIT
Feishu ToolsThinkInAIXYZ/deepchat6.4k—~652Automated safety check: PassApache-2.0
Feishu SetupAgentTeam-TaichuAI/ScienceClaw671—~425Automated safety check: PassNone
MCP Larkaahl/skills1621 repos~387Automated safety check: NotesMIT
Feishucodewhale-hq/Codewhale41k—~413Automated safety check: PassMIT
Sibyl Lark SyncSibyl-Research-Team/AutoResearch-SibylSystem283—~1.9kAutomated safety check: NotesNone

Similar skills

  • Feishu Tools

    ThinkInAIXYZ/deepchat

    Use the Feishu/Lark plugin MCP tools for Feishu documents, spreadsheets, knowledge content, and other matching workspace operations.

    6.4k GitHub stars~652 tokensUpdated today
    Productivity & AutomationAuto-check passed
  • Feishu Setup

    AgentTeam-TaichuAI/ScienceClaw

    自动配置飞书机器人应用。当用户要求配置飞书、创建飞书机器人、接入 Lark/飞书、设置飞书 appid/appsecret、或询问如何配置飞书 IM 时触发此 skill。该 skill 通过 sandbox 内置浏览器自动完成飞书开放平台上的应用创建、权限配置、事件订阅和发布,用户仅需扫码登录。

    671 GitHub stars~425 tokensUpdated 5 mo ago
    Productivity & AutomationAuto-check passed
  • MCP Lark

    aahl/skills

    Based on FeiShu(飞书) / Lark's OpenAPI MCP server, manage user information, chats, emails, cloud documents, multidimensional tables, tasks, calendars, etc.

    162 GitHub starsUsed in 1 repo~387 tokens
    Productivity & AutomationAuto-check: notes
  • Feishu

    codewhale-hq/Codewhale

    Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.

    41k GitHub stars~413 tokensUpdated today
    Productivity & AutomationAuto-check passed
  • Sibyl Lark Sync

    Sibyl-Research-Team/AutoResearch-SibylSystem

    Sibyl 飞书同步 agent - 将研究数据同步到飞书云空间

    283 GitHub stars~1.9k tokensUpdated 6 mo ago
    Productivity & AutomationAuto-check: notes
  • Feishu Doc

    openclaw/openclaw

    Feishu document read/write workflows. An agent skill from openclaw/openclaw.

    392k GitHub stars~516 tokensUpdated today
    Productivity & AutomationAuto-check passed

More from aAAaqwq/AGI-Super-Team

All 167 skills in this repo
  • Content Creator

    aAAaqwq/AGI-Super-Team

    Create SEO-optimized marketing content with consistent brand voice.

    105 GitHub starsUsed in 3 repos~1.9k tokens
    Auto-check passed
  • Financial Calculator

    aAAaqwq/AGI-Super-Team

    Advanced financial calculator with future value tables, present value, discount calculations, markup pricing, and compound interest.

    105 GitHub starsUsed in 1 repo~1.5k tokens
    Auto-check passed
  • Bankr Signals

    aAAaqwq/AGI-Super-Team

    Transaction-verified trading signals on Base blockchain. An agent skill from aAAaqwq/AGI-Super-Team.

    105 GitHub starsUsed in 2 repos~3.3k tokens
    Auto-check passed
  • Erc 8004

    aAAaqwq/AGI-Super-Team

    Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents).

    105 GitHub starsUsed in 2 repos~1.2k tokens
    Auto-check passed
  • Frontend Design Ultimate

    aAAaqwq/AGI-Super-Team

    Create distinctive, production-grade static sites with React, Tailwind CSS, and shadcn/ui — no mockups needed.

    105 GitHub starsUsed in 2 repos~2.7k tokens
    Auto-check passed
  • Zsxq Smart Publish

    aAAaqwq/AGI-Super-Team

    Publish and manage content on 知识星球 (zsxq.com). An agent skill from aAAaqwq/AGI-Super-Team.

    105 GitHub stars~1.5k tokensUpdated 2 days ago
    Auto-check passed

Questions about Feishu Automation

What does Feishu Automation do?

飞书(Lark)全通道自动化。使用 lark-mcp 工具操作飞书多维表格(Bitable)、发送消息、管理文档、创建群组、自动化工作流等。当用户需要操作飞书平台、同步数据到飞书表格、发送飞书通知、管理飞书文档或自动化飞书业务流程时使用此技能。. Feishu Automation is an agent skill from aAAaqwq/AGI-Super-Team.

When should I use Feishu Automation?

Feishu Automation fits situations like: tasks that involve Messaging and chat bots.

How do I install Feishu Automation in Claude Code?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a claude-code`. Or copy the skill folder (skills/feishu-automation in aAAaqwq/AGI-Super-Team) into .claude/skills/feishu-automation in your project. Claude Code loads it when a task matches its description.

How do I install Feishu Automation in Codex?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a codex`. Or copy the skill folder (skills/feishu-automation in aAAaqwq/AGI-Super-Team) into .agents/skills/feishu-automation in your project. Codex loads it when a task matches its description.

Can I use Feishu Automation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/feishu-automation, .gemini/skills/feishu-automation, .github/skills/feishu-automation and .opencode/skills/feishu-automation in your project.

What does Feishu Automation need to run?

Going by SKILL.md and its folder, Feishu Automation needs Python, a shell and JavaScript for the scripts in its folder, the command-line tools its instructions call (curl and python3) and credentials named FILE_TOKEN, DOC_TOKEN and APP_SECRET. Our summary lists: Python 3; Node.js; A Bash shell; A credential in YOUR_APP_SECRET; A credential in FILE_TOKEN. Its frontmatter pre-approves these tools: mcp__lark-mcp_*, Bash, Read, Write, Edit.

Does Feishu Automation access the network?

SKILL.md names 2 domains. In commands or code: open.feishu.cn and xxx.feishu.cn; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Feishu Automation safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Feishu Automation use?

Feishu Automation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Feishu Automation use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Feishu Automation?

Skills that share tags, products or a category with Feishu Automation: Feishu Tools (ThinkInAIXYZ/deepchat, 6.4k stars), Feishu Setup (AgentTeam-TaichuAI/ScienceClaw, 671 stars), MCP Lark (aahl/skills, 162 stars) and Feishu (codewhale-hq/Codewhale, 41k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Feishu Automation?

aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.

Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.