Feishu Tools
ThinkInAIXYZ/deepchat
Use the Feishu/Lark plugin MCP tools for Feishu documents, spreadsheets, knowledge content, and other matching workspace operations.
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。
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "feishu-automation" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automation into .claude/skills/feishu-automation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-automation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/feishu-automation .agents/skills/feishu-automation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "feishu-automation" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automation into .agents/skills/feishu-automation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-automation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/feishu-automation .cursor/skills/feishu-automation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "feishu-automation" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automation into .cursor/skills/feishu-automation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-automation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aAAaqwq/AGI-Super-Team.git --path skills/feishu-automation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/feishu-automation .gemini/skills/feishu-automation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "feishu-automation" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automation into .gemini/skills/feishu-automation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-automation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/feishu-automation .github/skills/feishu-automation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "feishu-automation" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automation into .github/skills/feishu-automation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-automation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aAAaqwq/AGI-Super-Team --skill feishu-automation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team feishu-automation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/feishu-automation .opencode/skills/feishu-automation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "feishu-automation" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/feishu-automation into .opencode/skills/feishu-automation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-automation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
feishu-automation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. 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.
11 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
mcp__lark-mcp_*BashReadWriteEditFrom allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python, Shell and JavaScript), which the agent can run.
Shell commands in SKILL.md call:
curlpython3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
open.feishu.cnxxx.feishu.cnFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
FILE_TOKENDOC_TOKENAPP_SECRETFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: mcp__lark-mcp_*, Bash, Read, Write, EditAutomated 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.
The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 321 words, ~2,261 tokens.
.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.使用 lark-mcp 工具实现飞书平台的全面自动化操作。
// 检查 lark-mcp 工具是否可用
// 可用工具前缀:mcp__lark-mcp_// 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!"
})
});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sendMessage - 发送消息getMessages - 获取消息历史replyMessage - 回复消息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。
# 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 $TOKEN" \
| python3 -c "import sys,json; d=json.load(sys.stdin); print(d.get('data',{}).get('result',{}).get('url',''))"支持的导入格式:
md → Markdowndocx → Word 文档xlsx → Excel 表格注意事项:
import_tasks/{ticket} 获取结果mount_type: 1 表示导入到"我的空间"https://xxx.feishu.cn/docx/{token}每次输出云文档时,必须完成以下步骤:
drive/v1/files/upload_alldrive/v1/import_tasksdrive/v1/permissions/{token}/public# 完整流程脚本
TOKEN=$(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createGroup - 创建群组addMember - 添加成员getGroupList - 获取群组列表getGroupInfo - 获取群组信息// 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()
}
});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"
}
]
}
]
})
});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));
}# 检查 .claude.json 中的 lark-mcp 配置
cat ~/.claude.json | grep -A 15 "lark-mcp"// 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!"
})
});© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 7 other files (scripts) in skills/feishu-automation of aAAaqwq/AGI-Super-Team.
Open the folder on GitHubat commit 7cefd81
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.
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Feishu Automation this skillaAAaqwq/AGI-Super-Team | 105 | 1 repos | ~2.3k | Automated safety check: Notes | MIT | |
| Feishu ToolsThinkInAIXYZ/deepchat | 6.4k | — | ~652 | Automated safety check: Pass | Apache-2.0 | |
| Feishu SetupAgentTeam-TaichuAI/ScienceClaw | 671 | — | ~425 | Automated safety check: Pass | None | |
| MCP Larkaahl/skills | 162 | 1 repos | ~387 | Automated safety check: Notes | MIT | |
| Feishucodewhale-hq/Codewhale | 41k | — | ~413 | Automated safety check: Pass | MIT | |
| Sibyl Lark SyncSibyl-Research-Team/AutoResearch-SibylSystem | 283 | — | ~1.9k | Automated safety check: Notes | None |
ThinkInAIXYZ/deepchat
Use the Feishu/Lark plugin MCP tools for Feishu documents, spreadsheets, knowledge content, and other matching workspace operations.
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。
aahl/skills
Based on FeiShu(飞书) / Lark's OpenAPI MCP server, manage user information, chats, emails, cloud documents, multidimensional tables, tasks, calendars, etc.
codewhale-hq/Codewhale
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
Sibyl-Research-Team/AutoResearch-SibylSystem
Sibyl 飞书同步 agent - 将研究数据同步到飞书云空间
openclaw/openclaw
Feishu document read/write workflows. An agent skill from openclaw/openclaw.
aAAaqwq/AGI-Super-Team
Create SEO-optimized marketing content with consistent brand voice.
aAAaqwq/AGI-Super-Team
Advanced financial calculator with future value tables, present value, discount calculations, markup pricing, and compound interest.
aAAaqwq/AGI-Super-Team
Transaction-verified trading signals on Base blockchain. An agent skill from aAAaqwq/AGI-Super-Team.
aAAaqwq/AGI-Super-Team
Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents).
aAAaqwq/AGI-Super-Team
Create distinctive, production-grade static sites with React, Tailwind CSS, and shadcn/ui — no mockups needed.
aAAaqwq/AGI-Super-Team
Publish and manage content on 知识星球 (zsxq.com). An agent skill from aAAaqwq/AGI-Super-Team.
Works with
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.
Feishu Automation fits situations like: tasks that involve Messaging and chat bots.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.