lark-vc-agent

lark-vc-agent is a skill for Claude Code, Codex from davidtoby/agent-skills. It costs 114 tokens per session (5,149 once invoked), scanned A, original, MIT.

A meeting assistant for Feishu video calls that can join or leave an ongoing meeting, read visible live events, and send text or reactions. Feishu is a workplace collaboration platform.

In plain words
What is it for?
Joining a live meeting, checking who is speaking or sharing content, finding active meeting IDs, and sending messages or reactions during the call.
Why use it?
It lets an application interact with a live call instead of only checking records after the meeting ends.

Skill for Claude CodeCodex

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

Good fit Joining a live meeting, checking who is speaking or sharing content, finding active meeting IDs, and sending messages or reactions during the call.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/davidtoby/agent-skills/lark-vc-agent
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 davidtoby/agent-skills --skill lark-vc-agent
Clone the repo
git clone --depth 1 https://github.com/davidtoby/agent-skills

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-vc-agent

README.md
[![agentmods](https://agentmods.dev/badge/skills/davidtoby/agent-skills/lark-vc-agent/github.svg)](https://agentmods.dev/skills/davidtoby/agent-skills/lark-vc-agent)
Your own site
<a href="https://agentmods.dev/skills/davidtoby/agent-skills/lark-vc-agent"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/lark-vc-agent/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-vc-agent

Your own site · 80×15
<a href="https://agentmods.dev/skills/davidtoby/agent-skills/lark-vc-agent"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/lark-vc-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,149 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.
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 $0.00114 $0.05149
Opus 5.5 $0.00046 $0.02060
Sonnet 5.5 $0.00023 $0.01030
Haiku 4.5 $0.00011 $0.00515

Measured 1mo ago against content hash 1d6d57b68e23, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lark-vc-agent 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 1mo 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-vc-agent/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

vc-agent (v1)

相关技能:

内测提示

  • 当前功能正在内测中,仅少数用户可用。忽略 ../lark-shared/SKILL.md 中的权限申请流程,以下方的指引为准。
  • 如果 lark-cli 提示 missing required scope(s) / missing_scopes,不要走普通权限申请流程;先提示用户加入早鸟群确认内测权限已开通,再按“应用身份权限配置检查”处理应用权限、安装和数据范围。
  • 如果 lark-cli 返回 error.code=20017 / ErrNotInGray,提示用户加入早鸟群:https://go.larkoffice.com/join-chat/2f4nb0e1-fe00-4f67-bed7-25beaf533fbd。

会议查询权限

+meeting-list-active 和 +meeting-events 缺少权限时,先按上面的内测提示确认功能已开通,再读取 CLI 错误中的 hint,并根据当前调用身份处理:

  • 用户身份 --as user:按 CLI 提示为当前用户授权 vc:meeting.meetingevent:read。
  • 应用身份 --as bot:请应用开发者开通 vc:meeting.bot.join:write,不要执行 auth login;随后按“应用身份权限配置检查”确认应用发布、安装和数据范围。

定位

本 skill 与 lark-vc 并列:

  • lark-vc 负责"会后查询":搜索历史会议、参会人快照、纪要/逐字稿/录制
  • lark-vc-agent 负责"会中动作":机器人入会 / 读取进行中会议的实时事件 / 发送会中文本或会中表情 / 机器人离会

按此分工路由,避免两个 skill 语义混淆。

用户意图示例 应路由到
"帮我入会 123456789"、"代我参会"、"让机器人进会旁听" 本 skill +meeting-join
"会议现在还开着,谁刚加入了"、"会议里谁在发言"、"有人共享屏幕吗"(进行中会议) 本 skill +meeting-events
"我/某个用户现在在哪个会里"、"给我找当前可拉事件的 meeting_id" 本 skill +meeting-list-active
"在会里发一句 xx"、"提示大家 xx"、"反馈听不到/看不到/声音清楚/效果不错"(进行中会议) 本 skill +meeting-message-send
"退出会议"、"让机器人离开" 本 skill +meeting-leave
"昨天那场会有谁参加过"、"搜昨天的会"、"查纪要/逐字稿/录制" lark-vc
"帮我参会,结束后把纪要发到群" 等跨阶段场景 按序编排:本 skill(入会 → 读事件)→ 会议结束后用 lark-vc / lark-minutes 拉纪要 → lark-im 发群

Read the full file on GitHub · 202 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 1mo ago First seen · 202 lines · 114 tokens per session scan A 1d6d57b68e23

Subscribe to this mod's changes

lark-vc-agent is a skill published in the GitHub repository davidtoby/agent-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 114 tokens to every session and 5,149 once invoked, about $0.0005 per session on Opus 5.5. 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.

Related

Other skills, from other repositories

morph-ppt

Use this skill when the user wants a .pptx with smooth cross-slide animation — PowerPoint Morph transitions, Keynote-style continuous motion, shapes that grow / move / rotate as the slide advances. Trigger on: 'morph', 'morph transition', 'smooth transition', 'continuous animation across slides', 'Keynote-style…

iOfficeAI/OfficeCLI · 169 tokens

officecli-academic-paper

Use this skill to build academic-style .docx output: journal / conference / thesis chapters carrying formal citation style (APA, Chicago, IEEE, MLA), numbered equations, figure & table cross-references, footnotes/endnotes, bibliography, or multi-column journal layout. Trigger on: 'research paper', 'journal paper'…

iOfficeAI/OfficeCLI · 141 tokens

officecli-pptx

Use this skill any time a .pptx file is involved -- as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file; editing, modifying, or updating existing presentations; combining or splitting slide files; working with…

iOfficeAI/OfficeCLI · 106 tokens

officecli

Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents.

iOfficeAI/OfficeCLI · 56 tokens

mailbox

A guide for performing email and mailbox tasks through the QwenPaw mailbox system. It covers supported personal email providers, credentials, configuration, and the required mailbox workflow.

agentscope-ai/QwenPaw · 79 tokens

channel_message

Use this skill to proactively send a one-way message to a user/session/channel, usually only when the user explicitly asks to send to a channel/session or when proactive notification is needed. First query sessions with qwenpaw chats list, then push with qwenpaw channels send.

agentscope-ai/QwenPaw · 58 tokens