Lark Workflow Standup Report logo

Lark Workflow Standup Report

OrganizationPopular
larksuite
lark-workflow-standup-report

日程待办摘要:编排 calendar +agenda 和 task +get-my-tasks,生成指定日期的日程与未完成任务摘要。适用于了解今天/明天/本周的安排。

Overview

Publisherlarksuite
Repositorycli
Skill namelark-workflow-standup-report
Stars
17.3K
Forks
1.4K
Bundled files
Instructions only
LicenseMIT
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 larksuite on GitHub. Read the source before you install it.

Installation

Install the Lark Workflow Standup Report 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.
  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/larksuite/cli.git /tmp/cli
mkdir -p .claude/skills
cp -r /tmp/cli/skills/lark-workflow-standup-report .claude/skills/lark-workflow-standup-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lark Workflow Standup Report 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 Standup Report 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 Standup Report 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.

日程待办摘要工作流

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

  • "今天有什么安排" / "今天的日程和待办"
  • "明天有什么会" / "明日日程与未完成任务"
  • "帮我看看今天要做什么" / "早报摘要"
  • "开工摘要" / "standup report"
  • "这周还有哪些安排"

前置条件

仅支持 user 身份。执行前确保已授权:

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

工作流

{date} ─┬─► calendar +agenda [--start/--end]              ──► 日程列表(会议/事件)
        └─► task +get-my-tasks --complete=false [--due-end] ──► 未完成待办列表
              AI 汇总(时间转换 + 冲突检测 + 排序)──► 摘要

Step 1: 获取日程

bash
# 今天(默认,无需额外参数)
lark-cli calendar +agenda

# 指定日期范围(必须使用 ISO 8601 格式,不支持 "tomorrow" 等自然语言)
lark-cli calendar +agenda --start "2026-03-26T00:00:00+08:00" --end "2026-03-26T23:59:59+08:00"

注意--start / --end 仅支持 ISO 8601 格式(如 2026-01-012026-01-01T15:04:05+08:00)和 Unix timestamp,不支持 "tomorrow""next monday" 等自然语言。需要 AI 根据当前日期自行计算目标日期。

输出包含:event_id、summary、start_time(含 timestamp + timezone)、end_time、free_busy_status、self_rsvp_status。

Step 2: 获取未完成待办

bash
# 默认 pending 摘要:必须显式过滤未完成任务(最多 20 条)
lark-cli task +get-my-tasks --complete=false

# 只看指定日期前到期的未完成任务(推荐用于摘要场景,减少数据量)
lark-cli task +get-my-tasks --complete=false --due-end "2026-03-27T23:59:59+08:00"

# 获取全部未完成任务(超过 20 条时)
lark-cli task +get-my-tasks --complete=false --page-all

注意+get-my-tasks 不带 --complete 时会同时返回已完成和未完成任务,会把已完成任务当成"待办"展示进摘要里。站会/日报这种 pending 汇总场景必须显式带上 --complete=false,不要省略。

数据量层面也建议加过滤:

  • --due-end 过滤出目标日期前到期的任务
  • 如果也需要无截止日期的任务,可不加 --due-end,但 AI 汇总时只展示近 30 天内创建的,其余折叠为"其他 N 项历史待办"

Step 3: AI 汇总

将 Step 1 和 Step 2 的结果整合,按以下结构输出:

## {日期}摘要({YYYY-MM-DD 星期X})

### 日程安排
| 时间 | 事件 | 组织者 | 状态 |
|------|------|--------|------|
| 09:00-10:00 | 产品需求评审 | 张三 | 已接受 |
| 14:00-15:00 | 技术方案讨论 | 李四 | 待确认 |

### 待办事项
- [ ] {task_summary}(截止:{due_date})
- [ ] {task_summary}

### 小结
- 共 {n} 场会议,{m} 项待办
- 冲突提醒:{列出时间重叠的日程}
- 空闲时段:{free_slots}(根据日程推算)

数据处理规则:

  1. 时间转换:API 返回 Unix timestamp,需根据 timezone 字段(通常为 Asia/Shanghai)转换为 HH:mm 格式
  2. RSVP 状态映射
    API 值显示文案
    accept已接受
    decline已拒绝
    needs_action待确认
    tentative暂定
  3. 日程排序:按开始时间升序排列
  4. 冲突检测:按时间排序后,检查相邻日程是否有时间重叠(前一个 end_time > 后一个 start_time),有则在小结中列出冲突组
  5. 已拒绝日程:标注"已拒绝"但不计入忙碌时段和冲突检测
  6. 待办排序:按截止时间升序,已过期的标注"已过期",无截止时间的排在最后

权限表

命令所需 scope
calendar +agendacalendar:calendar.event:read
task +get-my-taskstask:task:read

参考

Frequently asked questions

What does the Lark Workflow Standup Report AI skill do?

日程待办摘要:编排 calendar +agenda 和 task +get-my-tasks,生成指定日期的日程与未完成任务摘要。适用于了解今天/明天/本周的安排。

Why use Lark Workflow Standup Report on TypingMind?

Because you install it once and use it with any model. Lark Workflow Standup Report 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 Standup Report in TypingMind?

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

Which AI models can use Lark Workflow Standup Report?

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 Standup Report?

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

Is the Lark Workflow Standup Report AI skill free?

Yes. It is published on GitHub by larksuite under the MIT license. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇