lark-workflow-meeting-summary

lark-workflow-meeting-summary is a skill for Claude Code, Codex from appleweiping/WEIPING_WIKI. It costs 55 tokens per session (1,218 once invoked), scanned A, original, MIT.

A meeting-summary workflow for collecting notes from a selected time period and turning them into a structured report. It works with Feishu, a workplace collaboration platform.

In plain words
What is it for?
Use it to review meetings from a day, week, or other date range and produce a meeting report with summaries, tasks, and related sections.
Why use it?
It removes the need to search through separate meeting records and notes manually. It helps keep summaries and follow-up tasks together.

Skill for Claude CodeCodex

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

Good fit Use it to review meetings from a day, week, or other date range and produce a meeting report with summaries, tasks, and related sections.

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Install with agentmods
npx agentmods add skills/appleweiping/weiping_wiki/lark-workflow-meeting-summary
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.

Any agent
npx skills add appleweiping/WEIPING_WIKI --skill lark-workflow-meeting-summary
Clone the repo
git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI

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/appleweiping/weiping_wiki/lark-workflow-meeting-summary/github.svg)](https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-workflow-meeting-summary)
Your own site
<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-workflow-meeting-summary"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-workflow-meeting-summary/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for lark-workflow-meeting-summary

Your own site · 80×15
<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-workflow-meeting-summary"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-workflow-meeting-summary.svg" alt="Reviewed on agentmods" width="80" 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 1,218 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
  • 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 $0.01218
Opus 5 $0.00028 $0.00609
Sonnet 5 $0.00011 $0.00244
Haiku 4.5 $0.00006 $0.00122

Measured 8d ago against content hash 97b34c388538, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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

2 near-identical copies found in the catalogue:

skill/lark-cli/skills/lark-workflow-meeting-summary/SKILL.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 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。

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 +notes ──► 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
lark-cli vc +notes --meeting-ids "id1,id2,...,idN"   
  • 根据上一步搜集到的 meeting-id 查询会议纪要。
  • 单次最多查询 50 个纪要信息,超过 50 个需分批调用。
  • 部分会议返回 no notes available,在最终输出中标注"无纪要"
  • 记录每个会议的 note_doc_token(纪要文档 Token)和 verbatim_doc_token(逐字稿文档 Token)
  1. 获取纪要文档和逐字稿文档链接
# 学习命令使用方式
lark-cli schema drive.metas.batch_query

# 批量获取纪要文档与逐字稿链接: 一次最多查询 10 个文档
lark-cli drive metas batch_query --data '{"request_docs": [{"doc_type": "docx", "doc_token": "<doc_token>"}], "with_url": true}'

Step 4: 整理纪要报告

根据时间跨度选择输出格式:

  • 单日汇总("今天"/"昨天"):用"今日会议概览"标题,逐会议列出会议时间、主题、纪要链接、逐字稿链接。
  • 多日/周报("这周"/"过去 7 天"等):用"会议纪要周报"标题,含概览统计、逐会议详情。

Step 5: 生成文档(可选,用户要求时)

阅读 ../lark-doc/SKILL.md 学习云文档技能。

Read the full file on GitHub · 104 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 · 104 lines · 55 tokens per session scan A 97b34c388538

Subscribe to this mod's changes

lark-workflow-meeting-summary is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 16d ago), licensed MIT. It adds 55 tokens to every session and 1,218 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 2026-09-03.

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