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Lark Workflow Onboard

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liangdabiao
lark-workflow-onboard

新人入职向导:自动发送欢迎消息、添加到相关群聊、创建入职任务清单、设置日历提醒、通知HR和直属经理。一次触发,多系统联动。当用户需要'新人入职'、'入职引导'、'新员工入职'、'入职流程'、'欢迎新人'、'入职清单执行'时使用。

Overview

Publisherliangdabiao
Repositorylark-workflow-feishu-cli
Skill namelark-workflow-onboard
Stars
68
Forks
10
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by liangdabiao on GitHub. Read the source before you install it.

Installation

Install the Lark Workflow Onboard AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/liangdabiao/lark-workflow-feishu-cli/tree/main/.claude/skills/lark-workflow-onboard
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/liangdabiao/lark-workflow-feishu-cli.git /tmp/lark-workflow-feishu-cli
mkdir -p .claude/skills
cp -r /tmp/lark-workflow-feishu-cli/.claude/skills/lark-workflow-onboard .claude/skills/lark-workflow-onboard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lark Workflow Onboard in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lark Workflow Onboard on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lark Workflow Onboard is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

新人入职向导工作流

CRITICAL — 开始前 MUST 先用 Read 工具读取 ../lark-shared/SKILL.md,其中包含认证、权限处理

适用场景

  • "张三今天入职,帮他安排一下" / "新人入职"
  • "新人入职清单执行:张三,工程部" / "入职引导"
  • "帮我走一下新员工的入职流程" / "入职流程"
  • "新同事入职,帮他创建入职任务" / "欢迎新人"

前置条件

混合身份:user(拉群、创建任务、日程)和 bot(发消息)。

bash
lark-cli auth login --domain im,contact,task,calendar

工作流

{新员工信息: 姓名, 部门, 岗位, [HR open_id], [直属经理 open_id]}
  │
  ├── contact +search-user ─────────► 查找新员工 open_id
  │
  ├── im +messages-send ────────────► ① 发送欢迎消息
  │
  ├── im chat.members create ───────► ② 添加到部门群/项目群
  │
  ├── task +create ─────────────────► ③ 创建入职任务清单(串行,间隔 1s)
  │
  ├── calendar +create ─────────────► ④ 设置日历提醒
  │     ├── 30天试用期评估
  │     └── 团队迎新会
  │
  └── im +messages-send ────────────► ⑤ 通知 HR + 直属经理

Step 1: 查找新员工

bash
lark-cli contact +search-user --query "<新员工姓名>" --as user

从返回结果中提取 open_id(ou_xxx 格式)。如果查不到,提示用户提供姓名或 open_id。

Step 2: 发送欢迎消息

bash
lark-cli im +messages-send \
  --user-id "<new_user_open_id>" \
  --markdown "欢迎加入{公司/团队名}!

以下是入职指南:
1. 完成账号和权限初始化
2. 加入相关群聊
3. 领取办公设备
4. 了解团队协作方式

如有任何问题,随时联系你的导师或 HR。" \
  --as bot

注意:欢迎消息可根据部门和岗位自定义内容。可附加公司 wiki 链接、员工手册等资源。

Step 3: 添加到群聊

bash
# 先查看 schema 确认参数
lark-cli schema im.chat.members.create

# 添加到部门群(需要 user 身份)
lark-cli im chat.members create \
  --params '{"chat_id":"<dept_chat_id>","member_id_type":"open_id","succeed_type":1}' \
  --data '{"id_list":["<new_user_open_id>"]}' \
  --as user

如果需要添加到多个群,逐个调用,每次间隔 1 秒。

注意:

  • succeed_type: 1=不需要验证直接加入(适用于内部群)
  • 如果机器人不在群中,需要先将机器人拉入群
  • 对方必须是同一租户内的用户

Step 4: 创建入职任务清单

逐一创建入职任务(每次间隔 1 秒,避免频率限制):

bash
# 任务1:领取办公设备
lark-cli task +create \
  --summary "领取办公设备({姓名})" \
  --description "联系 IT 部门领取笔记本电脑、显示器等办公设备" \
  --due "<7天后日期>" \
  --as user

# 任务2:完成入职培训
lark-cli task +create \
  --summary "完成入职培训({姓名})" \
  --description "完成公司在线培训课程,包括安全培训、合规培训等" \
  --due "<14天后日期>" \
  --as user

# 任务3:认识团队成员
lark-cli task +create \
  --summary "认识团队成员({姓名})" \
  --description "与团队成员逐一交流,了解协作方式和项目背景" \
  --due "<7天后日期>" \
  --as user

# 任务4:完成试用期目标设定
lark-cli task +create \
  --summary "完成试用期目标设定({姓名})" \
  --description "与直属经理讨论并确定试用期工作目标和考核标准" \
  --due "<14天后日期>" \
  --as user

注意:--due 使用系统 date 命令计算目标日期,不要心算。任务创建后记录 task_id。

Step 5: 设置日历提醒

bash
# 30天试用期评估提醒
lark-cli calendar +create \
  --summary "30天试用期评估 - {姓名}" \
  --start "<30天后 10:00>" \
  --end "<30天后 11:00>" \
  --as user

# 团队迎新会(如适用)
lark-cli calendar +create \
  --summary "团队迎新会 — 欢迎{姓名}" \
  --start "<本周五 15:00>" \
  --end "<本周五 16:00>" \
  --attendee-ids "<new_user_open_id>,<manager_open_id>" \
  --as user

注意:创建日程前与用户确认时间和内容,避免误操作。

Step 6: 通知 HR 和直属经理

bash
# 通知 HR
lark-cli im +messages-send \
  --user-id "<hr_open_id>" \
  --markdown "新员工入职通知

姓名:{姓名}
部门:{部门}
岗位:{岗位}
入职日期:{日期}

入职引导已完成以下操作:
- 已发送欢迎消息
- 已添加到部门群
- 已创建入职任务清单
- 已设置试用期评估提醒" \
  --as bot

# 通知直属经理
lark-cli im +messages-send \
  --user-id "<manager_open_id>" \
  --markdown "您团队的新成员 {姓名} 今日入职!

已为 {姓名} 创建了入职任务清单和试用期评估提醒。
请在本周内与 {姓名} 讨论试用期目标。" \
  --as bot

降级策略

场景降级方案
查不到新员工提示用户提供 open_id
群聊添加失败列出失败群聊,让用户手动添加
任务创建频率限制降低创建速度,间隔 2 秒
日程创建失败仅创建任务,日程让用户手动添加
HR/经理 open_id 未知询问用户提供,或跳过通知步骤

权限表

命令所需 scope
contact +search-usercontact:user.base:readonly
im +messages-sendim:message
im chat.members createim:chat.member:write
task +createtask:task:write
calendar +createcalendar:calendar:write, calendar:event:write

参考

Frequently asked questions

What does the Lark Workflow Onboard AI skill do?

新人入职向导:自动发送欢迎消息、添加到相关群聊、创建入职任务清单、设置日历提醒、通知HR和直属经理。一次触发,多系统联动。当用户需要'新人入职'、'入职引导'、'新员工入职'、'入职流程'、'欢迎新人'、'入职清单执行'时使用。

Why use Lark Workflow Onboard on TypingMind?

Because you install it once and use it with any model. Lark Workflow Onboard is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lark Workflow Onboard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/liangdabiao/lark-workflow-feishu-cli/tree/main/.claude/skills/lark-workflow-onboard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Lark Workflow Onboard?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lark Workflow Onboard?

As many as you like. As long as a model supports skills, you can use Lark Workflow Onboard with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lark Workflow Onboard AI skill free?

It is published on GitHub by liangdabiao. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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