lark-workflow-standup-report

lark-workflow-standup-report is a skill for Claude Code, Codex from DropFan/claude-code-plugins. It costs 53 tokens per session (1,665 once invoked), scanned A, original, MIT.

A Feishu (Lark) workflow that combines calendar events with unfinished tasks into a daily schedule summary. Feishu is a workplace collaboration app with calendar and task features.

In plain words
What is it for?
Use it for today, tomorrow, or weekly work summaries, including scheduled events and tasks that are not complete.
Why use it?
It puts meetings and open tasks in one view, including time conversion, conflict checks, and ordering.

Skill for Claude CodeCodex

Part of the lark plugin — 27 skills, 2 agents shipped together

Install

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.

agentmods
npx agentmods add skills/dropfan/claude-code-plugins/lark-workflow-standup-report
Any agent
npx skills add DropFan/claude-code-plugins --skill lark-workflow-standup-report
Clone the repo
git clone --depth 1 https://github.com/DropFan/claude-code-plugins

Made for: Claude Code, Codex.

Or install lark, the plugin that ships this one along with the rest of its 27 skills, 2 agents.

Wrote 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.

agentmods badge for lark-workflow-standup-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/dropfan/claude-code-plugins/lark-workflow-standup-report.svg)](https://agentmods.dev/skills/dropfan/claude-code-plugins/lark-workflow-standup-report)
Your own site
<a href="https://agentmods.dev/skills/dropfan/claude-code-plugins/lark-workflow-standup-report"><img src="https://agentmods.dev/badge/skills/dropfan/claude-code-plugins/lark-workflow-standup-report.svg" alt="Measured on agentmods" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,665 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00053 $0.01665
Opus 5 $0.00026 $0.00833
Sonnet 5 $0.00011 $0.00333
Haiku 4.5 $0.00005 $0.00167

Measured 5d ago against content hash a7b223bf49e3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 5d 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.

plugins/lark/skills/lark-workflow-standup-report/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

⚙️ Cowork / Claude Desktop 执行环境说明(自动注入)

本技能依赖本地 lark-cli@larksuite/cli,可用 command -v lark-cli 定位)及其 ~/.lark-cli 登录态(应用密钥存于 macOS keychain)。

在 Cowork 中运行任何 lark-cli 命令时,必须在本地 macOS 上执行(使用 Desktop Commander 的 start_process / interact_with_process,或其它本地 shell 工具),不要用隔离的 Linux 沙箱 mcp__workspace__bash——沙箱里没有 lark-cli、也读不到 keychain。 执行前确保 npm 全局 bin 目录(npm prefix -g 输出目录下的 bin)在 PATH 中。

(在 Claude Code 中可忽略本说明,lark-cli 在本机 shell 直接可用。)

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 2026-01-012026-01-01T15:04:05+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

# 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"

Read the full file on GitHub · 134 lines

Changes

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.

  1. 5d ago First seen · 134 lines · 53 tokens per session scan A a7b223bf49e3

Subscribe to this mod's changes

lark-workflow-standup-report is a skill published in the GitHub repository DropFan/claude-code-plugins (7 stars, last pushed 29d ago), licensed MIT. It adds 53 tokens to every session and 1,665 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 2026-08-31.