Lark CLI is a command-line tool for using Lark/Feishu services such as messaging, documents, spreadsheets, calendars, mail, tasks, and meetings. It is intended for people and AI agents that need to work with these business tools through terminal commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/larksuite/cli/lark-workflow-standup-reportnpx skills add larksuite/cli --skill lark-workflow-standup-reportgit clone --depth 1 https://github.com/larksuite/cliWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/larksuite/cli/lark-workflow-standup-report)<a href="https://agentmods.dev/skills/larksuite/cli/lark-workflow-standup-report"><img src="https://agentmods.dev/badge/skills/larksuite/cli/lark-workflow-standup-report.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.01437 |
| Opus 5 | $0.00026 | $0.00718 |
| Sonnet 5 | $0.00011 | $0.00287 |
| Haiku 4.5 | $0.00005 | $0.00144 |
Grade A, and why
lark-workflow-standup-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- lark-workflow-standup-report — 100% identical, 0 lines differ
- lark-workflow-standup-report — 91% identical, 22 lines differ
- lark-workflow-standup-report — 91% identical, 22 lines differ
- lark-workflow-standup-report — 91% identical, 22 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
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
# 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2026-01-01或2026-01-01T15:04:05+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
# 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:
- 用
--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)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 123 lines · 53 tokens per session scan A a283de746e65
lark-workflow-standup-report is a skill published in the GitHub repository larksuite/cli (17,026 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 1,437 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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