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/dropfan/claude-code-plugins/lark-workflow-meeting-summarynpx skills add DropFan/claude-code-plugins --skill lark-workflow-meeting-summarygit clone --depth 1 https://github.com/DropFan/claude-code-pluginsWrote 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/dropfan/claude-code-plugins/lark-workflow-meeting-summary)<a href="https://agentmods.dev/skills/dropfan/claude-code-plugins/lark-workflow-meeting-summary"><img src="https://agentmods.dev/badge/skills/dropfan/claude-code-plugins/lark-workflow-meeting-summary.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 | $0.00055 | $0.01949 |
| Opus 5 | $0.00028 | $0.00975 |
| Sonnet 5 | $0.00011 | $0.00390 |
| Haiku 4.5 | $0.00006 | $0.00195 |
Grade A, and why
lark-workflow-meeting-summary 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.
This is a copy
86% identical to lark-workflow-meeting-summary — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 133 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。)
会议纪要汇总工作流
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。然后阅读 ../lark-vc/SKILL.md,了解会议纪要相关操作。
CRITICAL — 开始前 MUST 先用 Read 工具读取 ../lark-vc/references/vc-domain-boundaries.md,不读将导致命令使用、会议产物决策、领域边界职责判断错误:
- 了解日历 & VC、会议产物 & 文档的关联关系和职责划分
- 了解会议产物(妙记和纪要)之间的关联关系,例如:妙记和纪要产生条件相互独立
- 了解不同会议产物的组成部分,以便根据需求决策使用哪种产物的数据
- 了解会议总结、分析和信息提取的标准流程
适用场景
- "帮我整理这周的会议纪要" / "总结最近的会议" / "生成会议周报"
- "看看今天开了哪些会" / "回顾过去一周开了哪些会"
前置条件
仅支持 user 身份。执行前确保已授权:
lark-cli auth login --domain vc # 基础(查询+纪要)
lark-cli auth login --domain vc,drive # 含读取纪要文档正文、生成文档
工作流
{时间范围} ─► vc +search ──► 会议列表 (meeting_ids)
│
▼
vc +detail ──► 获取 note_id
│
▼
note +detail ──► 纪要文档 tokens
│
▼
drive metas batch_query 纪要元数据
│
▼
结构化报告
Step 1: 确定时间范围
默认过去 7 天。推断规则:"今天"→当天,"这周"→本周一now,"上周"→上周一上周日,"这个月"→1日~now。
注意:日期转换必须调用系统命令(如
date),不要心算。时间范围参数需根据 CLI 实际要求格式化(通常为YYYY-MM-DD或 ISO 8601)。
Step 2: 查询会议记录
# page-size 最大为 30
lark-cli vc +search --start "<YYYY-MM-DD>" --end "<YYYY-MM-DD>" --format json --page-size 30
- 时间范围拆分:搜索的时间范围最大为 1 个月。搜索更长时间范围的会议,需要拆分为多次时间范围为一个月查询。
--end为包含当天的日期(即查"今天"时 start 和 end 都填今天)--format json输出 JSON 格式,你更佳擅长解析 JSON 数据。--page-size 30每页最多 30 条。- 有
page_token时必须继续翻页,收集所有id字段(meeting-id)
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.
- 5d ago First seen · 133 lines · 55 tokens per session scan A bd5259379cfe
lark-workflow-meeting-summary is a skill published in the GitHub repository DropFan/claude-code-plugins (7 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,949 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to lark-workflow-meeting-summary, differing in 13 lines, and is treated as a copy.
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