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
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlark-vcExecute the skills CLI command in your project's root directory to begin installation:
Fetches lark-vc from larksuite/cli and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate lark-vc. Access via /lark-vc in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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
note_doc_token)内容时,纪要文档的第一个 <whiteboard> 标签是封面图(AI 生成的总结可视化),应同时下载展示给用户:# 1. 读取纪要内容
lark-cli docs +fetch --doc <note_doc_token>
# 2. 从返回的 markdown 中提取第一个 <whiteboard token="xxx"/> 的 token
# 3. 下载封面图到 artifact 目录(和逐字稿同目录,保持产物归拢)
# 并非所有纪要都有封面画板,没有 <whiteboard> 标签时跳过即可
lark-cli docs +media-download --type whiteboard --token <whiteboard_token> --output ./artifact-<title>/cover
产物目录规范:同一会议的所有下载产物(封面图、逐字稿等)统一放到
artifact-<title>/目录下,不要散落在当前工作目录。
note_doc_tokenvsverbatim_doc_token— 两份不同的文档,根据用户意图选择:
note_doc_token→ 智能纪要(AI 总结 + 待办 + 章节)— 用户说"纪要""总结""待办""纪要内容"时用这个verbatim_doc_token→ 逐字稿(完整的逐句文字记录,含说话人和时间戳)— 用户说"逐字稿""完整记录""谁说了什么"时用这个- 用户意图不明确时,应展示两个文档链接让用户选择,而不是替用户决定
lark-cli drive metas batch_query 查询# 学习命令使用方式
lark-cli schema drive.metas.batch_query
# 批量获取文档基本信息: 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}'
lark-cli docs +fetch。# 获取文档内容
lark-cli docs +fetch --doc <doc_token>
Meeting (视频会议)
├── Note (会议纪要)
│ ├── MainDoc (主纪要文档)
│ ├── VerbatimDoc (逐字稿)
│ └── SharedDoc (会中共享文档)
└── Minutes (妙记)
├── Transcript (文字记录)
├── Summary (总结)
├── Todos (待办)
└── Chapters (章节)
注意:
+search只能查询已结束的历史会议。查询未来的日程安排请使用 lark-calendar。优先级:当用户搜索历史会议时,应优先使用
vc +search而非calendar events search。calendar 的搜索面向日程,vc 的搜索面向已结束的会议记录,支持按参会人、组织者、会议室等维度过滤。路由规则:如果用户在问“开过的会”“今天开了哪些会”“最近参加过什么会”“已结束的会议”“历史会议记录”,优先使用
vc +search。只有在查询未来日程、待开的会、agenda 时才优先使用 lark-calendar。特殊情况: 当用户查询“今天有哪些会议”时,通过
vc +search查询今天开过的会议记录,同时使用 lark-calendar 技能查询今天还未开始的会议,统一整理后展示给用户。
Shortcut 是对常用操作的高级封装(lark-cli vc +<verb> [flags])。有 Shortcut 的操作优先使用。
| Shortcut | 说明 |
|---|---|
+search |
Search meeting records (requires at least one filter) |
+notes |
Query meeting notes (via meeting-ids, minute-tokens, or calendar-event-ids) |
lark-cli schema vc.<resource>.<method> # 调用 API 前必须先查看参数结构
lark-cli vc <resource> <method> [flags] # 调用 API
重要:使用原生 API 时,必须先运行
schema查看--data/--params参数结构,不要猜测字段格式。
get — 获取会议详情(主题、时间、参会人、note_id)# 获取会议基础信息:不包含参会人列表
lark-cli vc meeting get --params '{"meeting_id": "<meeting_id>"}'
# 获取会议基础信息:包含参会人列表
lark-cli vc meeting get --params '{"meeting_id": "<meeting_id>", "with_participants": true}'
get — 获取妙记基础信息(标题、时长、封面);查询纪要内容请用 +notes --minute-tokens <minute-token>| 方法 | 所需 scope |
|---|---|
+notes --meeting-ids |
vc:meeting.meetingevent:read、vc:note:read |
+notes --minute-tokens |
vc:note:read、minutes:minutes:readonly、minutes:minutes.artifacts:read、minutes:minutes.transcript:export |
+notes --calendar-event-ids |
calendar:calendar:read、calendar:calendar.event:read、vc:meeting.meetingevent:read、vc:note:read |
+search |
vc:meeting.search:read |
meeting.get |
vc:meeting.meetingevent:read |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
lark-vc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: lark-vc is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for lark-vc matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: lark-vc is focused, and the summary matches what you get after install.
lark-vc has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for lark-vc matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: lark-vc is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added lark-vc from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
lark-vc has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: lark-vc is focused, and the summary matches what you get after install.
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