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.
git clone --depth 1 https://github.com/davidtoby/agent-skillsnpx agentmods add skills/davidtoby/agent-skills/lark-vcWrote 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/davidtoby/agent-skills/lark-vc)<a href="https://agentmods.dev/skills/davidtoby/agent-skills/lark-vc"><img src="https://agentmods.dev/badge/skills/davidtoby/agent-skills/lark-vc.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 5.1 | $0.00095 | $0.04440 |
| Opus 5 | $0.00048 | $0.02220 |
| Sonnet 5 | $0.00019 | $0.00888 |
| Haiku 4.5 | $0.00010 | $0.00444 |
Grade A, and why
lark-vc 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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- lark-vc — 95% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
vc (v1)
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
CRITICAL — 开始前 MUST 先用 Read 工具读取 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
身份
所有 vc 命令默认使用 --as user。+search 和 meeting get 也支持 --as bot。
# BAD — 查昨天的会议用 calendar，会漏掉即时会议
lark-cli calendar +search-event --query "站会" --start <start_time> --end <end_time>
# GOOD — 查已结束的会议用 vc +search
lark-cli vc +search --query "站会" --start <start_time> --end <end_time>
Shortcuts （推荐优先使用）
| Shortcut | 说明 |
|---|---|
+search |
搜索历史会议记录（需至关键词、时间范围、组织者、参与者、会议室少一个筛选条件） |
+detail |
通过 meeting-ids 获取会议详情，包括 note_id 和 minute_token |
+recording |
通过 meeting-ids 或 calendar-event-ids 查询 minute_token |
- 使用任何 Shortcut 前，必须先读其对应 reference 文档。
意图路由
| 用户意图 | 路由到 |
|---|---|
| 查"昨天的会议""上周的会""已结束的会议" | 本 skill（+search，含即时会议） |
| 查日历/日程或未来时间的会议 | lark-calendar |
| 查"今天有哪些会议" | vc +search（已结束）+ lark-calendar（未开始），合并展示 |
| 只按自然语言标题查"xx 纪要的逐字稿 / 原始记录 / 谁说了什么" | 先到 lark-drive / lark-doc；仅在已拿到 note_id / vc-node-id 后再到 lark-note |
| Agent 真实入会/离会、会中实时事件 | lark-vc-agent |
| 妙记信息/时长/封面/链接 | 先走 vc +detail 或 vc +recording 获取 minute_token，再用 lark-minutes 的 minutes get |
| 本地音视频文件转纪要/逐字稿 | 先走 lark-minutes 上传，再用 minutes +detail --minute-tokens |
核心概念
- 视频会议（Meeting）：飞书视频会议实例，通过 meeting_id 标识。已结束的会议支持通过关键词、时间段、参会人、组织者、会议室等条件搜索（见
+search）。 - 会议纪要（Note）：视频会议结束后生成的结构化文档，通过
note_id标识，包含纪要文档（总结、待办）和逐字稿文档。note_display_type区分**普通纪要（normal）**和 unified 纪要；已知note_id的直查与 unified 原始记录请用 lark-note。 - 妙记（Minutes）：来源于飞书视频会议的录制产物或用户上传的音视频文件，支持视频/音频的转写，包含总结、待办、章节和文字记录，通过 minute_token 标识。妙记带有原始会议录制视频，会后不会自动授权给参会人，需管理员授权或参会人主动申请；而智能纪要及其逐字稿会后自动授权给参会人。
- 纪要文档（MainDoc）：AI 智能纪要的主文档，包含 AI 生成的总结和待办，对应
note_doc_token。 - 用户会议纪要（MeetingNotes）：用户主动绑定到日程的纪要文档，对应
meeting_note。需先通过calendar +meeting由event_id获取。 - 逐字稿（VerbatimDoc）：会议的逐句文字记录，包含说话人和时间戳。
What ships with it
4 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.
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.
- 4d ago First seen · 206 lines · 95 tokens per session scan A 07663b7ba87a
lark-vc is a skill published in the GitHub repository davidtoby/agent-skills (10 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 4,440 once invoked, about $0.0005 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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