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 skills add ddpie/lark-mcp-on-agentcore --skill lark-minutesgit clone --depth 1 https://github.com/ddpie/lark-mcp-on-agentcoreWrote 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/ddpie/lark-mcp-on-agentcore/lark-minutes)<a href="https://agentmods.dev/skills/ddpie/lark-mcp-on-agentcore/lark-minutes"><img src="https://agentmods.dev/badge/skills/ddpie/lark-mcp-on-agentcore/lark-minutes/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.
<a href="https://agentmods.dev/skills/ddpie/lark-mcp-on-agentcore/lark-minutes"><img src="https://agentmods.dev/badge/skills/ddpie/lark-mcp-on-agentcore/lark-minutes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00115 | $0.03500 |
| Opus 5 | $0.00057 | $0.01750 |
| Sonnet 5 | $0.00023 | $0.00700 |
| Haiku 4.5 | $0.00012 | $0.00350 |
Grade A, and why
lark-minutes 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
minutes (v1)
CRITICAL — 开始前 MUST 先调用 lark_get_skill(domain="vc", section="vc-domain-boundaries")，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
Shortcuts
| Shortcut | 说明 |
|---|---|
lark_minutes_search |
按关键词、所有者、参与者、时间范围搜索妙记 |
lark_minutes_detail |
查询妙记详情(标题和关联的纪要note_id)，按需获取 AI 产物（总结、待办、章节、逐字稿、关键词） |
lark_minutes_download |
下载妙记音视频媒体文件 |
lark_minutes_upload |
上传 file_token 生成妙记 |
lark_minutes_update |
更新妙记标题 |
lark_minutes_speaker_replace |
替换妙记逐字稿中的说话人（须先用 lark_invoke 裸调 speakerlist 取 speaker_id） |
lark_minutes_word_replace |
批量替换逐字稿关键词 |
lark_minutes_summary |
替换妙记 AI 总结全文 |
lark_minutes_todo |
新建/更新/删除妙记 AI 待办（单条或 todos 批量；不是 lark-task） |
- 使用任何 Shortcut 前，必须先调用对应的
lark_get_skill(domain="minutes", section="...")了解参数和返回值结构。
意图路由
| 用户意图 | 命令 |
|---|---|
| 我的妙记 / 搜索妙记 / 某段时间的妙记 | lark_minutes_search |
| 妙记基础信息：标题 / 时长 / 封面 / 链接 | lark_invoke(tool_name="lark_minutes_minutes_get", ...) |
| 下载妙记音视频文件、获取媒体下载链接 | lark_minutes_download（仅媒体；要妙记内容用 lark_minutes_detail） |
| 妙记总结 / 章节 / 待办 / 关键词 / 逐字稿 | lark_minutes_detail(minute_tokens="<token>") + 显式产物 flag |
| 基于妙记提炼/总结/分析/回顾会议 | lark_minutes_detail(minute_tokens="<token>", transcript=true)，再独立分析（禁止照搬 AI 总结） |
拿这条妙记关联的纪要文档（note_doc_token / verbatim_doc_token / shared_doc_tokens） |
lark_minutes_detail 取顶层 note_id → lark_note_detail(note_id="...") |
| 把本地音视频转纪要 / 逐字稿 / 文字稿 | lark_drive_upload 取 file_token → lark_minutes_upload 生成 minute_url → lark_minutes_detail 拿产物 |
| 在妙记里增加 / 更改 / 删除 AI 待办 | lark_minutes_todo（禁止走 lark-task） |
| 替换妙记的AI 总结 | lark_minutes_summary |
| 重命名妙记/改妙记标题 | lark_minutes_update |
| 替换说话人/把 A 的发言改成 B/重新归属发言人/把外部（非飞书）说话人改成飞书用户 | 先用 lark_invoke(tool_name="lark_api_GET", ...) 裸调 .../transcript/speakerlist 取 speaker_id，再 lark_minutes_speaker_replace；from_speaker_id 只传 id，不传展示名 |
| 批量替换逐字稿关键词 | lark_minutes_word_replace |
| 用户同时提到"会议/开会"和"妙记" | 先 lark-vc（lark_vc_search → lark_vc_recording）获取 minute_token，再本 skill |
What ships with it
8 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.
- references/lark-minutes-detail.md 2.6 KB
- references/lark-minutes-download.md 4.7 KB
- references/lark-minutes-search.md 7.5 KB
- references/lark-minutes-speaker-replace.md 4.6 KB
- references/lark-minutes-summary.md 3.8 KB
- references/lark-minutes-todo.md 4.3 KB
- references/lark-minutes-update.md 943 B
- references/lark-minutes-upload.md 4.4 KB
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.
- 10d ago First seen · 182 lines · 115 tokens per session scan A eb9cd15299be
lark-minutes is a skill published in the GitHub repository ddpie/lark-mcp-on-agentcore (8 stars, last pushed 13d ago), licensed MIT. It adds 115 tokens to every session and 3,500 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
larksnap-fetch
A bridge for downloading Feishu/Lark documents or ordinary webpages into local files, with options such as Markdown, HTML, or PDF. Feishu, also called Lark, is a workplace collaboration platform.
lark-cli
A command-line tool for working with Lark, also called Feishu, a workplace collaboration platform. It covers services such as calendars, meetings, documents, spreadsheets, messaging, tasks, approvals, and shared files.
lark-wiki-migration
A Feishu wiki migration tool copies all document pages from one Feishu knowledge base to another. Feishu is a workplace collaboration platform, and a wiki is an organized collection of linked documents.
documents
Read and write Lark documents - get content as markdown or blocks, create new documents, append content (text, headings, lists, code), list folders. Use when user asks about a Lark doc, wants to read/create/edit a document, or mentions a document URL/ID.
sheets
Read and query Lark Sheets (spreadsheets) - list sheets in a spreadsheet, read cell data. Use when user asks about a spreadsheet, wants to read data from a Lark sheet, or mentions a spreadsheet URL/ID.
minutes
Access Lark Minutes recordings - get metadata, export transcripts, download audio/video. Use when user asks about meeting recordings, transcripts, or minutes.