lark-workflow-meeting-summary

lark-workflow-meeting-summary is a skill for Claude Code, Codex from larksuite/cli. It costs 55 tokens per session (2,069 once invoked), scanned A, original, MIT.

A workflow that finds meetings in a chosen time range, opens their notes, and combines them into a structured report.

In plain words
What is it for?
Use it to organise meeting notes, prepare a weekly meeting report, or review meetings from today, last week, or another selected period.
Why use it?
Meeting information can be spread across search results, meeting details, notes, and documents. This gathers those parts into one reviewable summary.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is 逐字稿会落盘,供 Step 4 基于原始发言独立提炼(不要照搬 AI 总结)。若返回 `No read permission`(`2091005`),先把无权限事实告知用户,用户明确同意后再用单数 flag 申请:`lark-cli minutes +apply-permission --minute-token "<.

not rated 17krepo +119 today A scan Socket: passSnyk: failSkillSpector: pass 55 tokens original MIT

Good fit Use it to organise meeting notes, prepare a weekly meeting report, or review meetings from today, last week, or another selected period.

Compare 6 skills from other repositories ↓
About the project

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.

larksuite/cli · 17,058 stars · on GitHub

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/larksuite/cli
agentmods
npx agentmods add skills/larksuite/cli/lark-workflow-meeting-summary

Made for: Claude Code, Codex.

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-meeting-summary

README.md
[![agentmods](https://agentmods.dev/badge/skills/larksuite/cli/lark-workflow-meeting-summary.svg)](https://agentmods.dev/skills/larksuite/cli/lark-workflow-meeting-summary)
Your own site
<a href="https://agentmods.dev/skills/larksuite/cli/lark-workflow-meeting-summary"><img src="https://agentmods.dev/badge/skills/larksuite/cli/lark-workflow-meeting-summary.svg" alt="Measured on agentmods" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,069 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 25 Apr 2026
  • Snyk fail 25 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00055 $0.02069
Opus 5 $0.00028 $0.01035
Sonnet 5 $0.00011 $0.00414
Haiku 4.5 $0.00006 $0.00207

Measured 8d ago against content hash 2cc95a5db67b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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 8d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/lark-workflow-meeting-summary/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

会议纪要汇总工作流

CRITICAL — 开始前 MUST 先完整读取 ../lark-shared/SKILL.md../lark-meeting/SKILL.md。认证、身份和权限以 lark-shared 为准;会议与产物关系、产物选择和逐字稿路由以 lark-meeting 为准。

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
lark-cli auth login --domain vc,drive,minutes  # 含无 note_id 时的妙记备选路径

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。
  • page_token 时必须继续翻页,收集所有 id 字段(meeting-id)

Step 3: 获取纪要元数据

  1. 查询会议关联的纪要信息
# 首先获取 note_id 和 minute_token
lark-cli vc +detail --meeting-ids "id1,id2,...,idN"

# 然后用 note_id 获取文档 tokens(如有多个需分别获取)
lark-cli note +detail --note-id "note_id"
  • 根据上一步搜集到的 meeting-id 查询。
  • 单次最多查询 50 个,超过 50 个需分批调用。
  • 部分会议没有 note_id 或报错 no notes available不要直接标注"无纪要":先看 vc +detail 是否返回了 minute_token,有则走下面的妙记备选路径;note_idminute_token 都没有时才标注"无纪要"。
  • 记录每个纪要的 note_id(纪要 ID)、note_display_type(展示类型:unknown / normal / unified)、note_doc_token(纪要文档 Token)和 verbatim_doc_token(逐字稿文档 Token)。

Read the full file on GitHub · 130 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. 8d ago First seen · 130 lines · 55 tokens per session scan A 2cc95a5db67b

Subscribe to this mod's changes

lark-workflow-meeting-summary is a skill published in the GitHub repository larksuite/cli (17,058 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 2,069 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.