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 yokingma/weclaws --skill lark-whiteboardgit clone --depth 1 https://github.com/yokingma/weclawsWrote 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/yokingma/weclaws/lark-whiteboard)<a href="https://agentmods.dev/skills/yokingma/weclaws/lark-whiteboard"><img src="https://agentmods.dev/badge/skills/yokingma/weclaws/lark-whiteboard/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/yokingma/weclaws/lark-whiteboard"><img src="https://agentmods.dev/badge/skills/yokingma/weclaws/lark-whiteboard.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00194 | $0.02135 |
| Opus 5 | $0.00097 | $0.01068 |
| Sonnet 5 | $0.00039 | $0.00427 |
| Haiku 4.5 | $0.00019 | $0.00214 |
Grade A, and why
lark-whiteboard 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.
This is a copy
100% identical to lark-whiteboard — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT]
- 运行
lark-cli --version，确认可用，无需询问用户。- 运行
npx -y @larksuite/whiteboard-cli@^0.2.11 -v，确认可用，无需询问用户。
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
快速决策
| 用户需求 | 行动 |
|---|---|
| 查看画板内容 / 导出图片 | +query --output_as image |
| 获取画板的 Mermaid/PlantUML 代码 | +query --output_as code |
| 检查画板是否由代码绘制 | +query --output_as code |
| 修改节点文字/颜色（简单改动） | +query --output_as raw → 手动改 JSON → +update --input_format raw |
| 用户已提供 Mermaid/PlantUML 代码，或明确指定用该格式 | 自己生成/使用代码 → +update --input_format mermaid/plantuml |
| 绘制复杂图表（架构/流程/组织等） | → § 创作 Workflow |
| 修改/重绘已有复杂画板 | → § 修改 Workflow |
⚠️ 强制规范（通过 stdin 更新）： 数据来源于本地文件时，必须使用
--source - --input_format <格式>。 例：cat chart.mmd | lark-cli whiteboard +update <token> --source - --input_format mermaid
Shortcuts
| Shortcut | 说明 |
|---|---|
+query |
查询画板，导出为预览图片、代码或原始节点结构 |
+update |
更新画板，支持 PlantUML、Mermaid 或 OpenAPI 原生格式 |
创作 Workflow
此 workflow 用于独立创作一个画板。 需要在文档中批量创建多个画板时，由 lark-doc 负责调度，见
lark-doc技能的references/lark-doc-whiteboard.md。
Step 1：获取 board_token
| 用户给了什么 | 怎么获取 |
|---|---|
直接给了 whiteboard token（wbcnXXX） |
直接使用 |
| 文档 URL 或 doc_id，文档中已有画板 | lark-cli docs +fetch --api-version v2 --doc <URL> --as user，从返回的 <whiteboard token="xxx"/> 提取 |
| 文档 URL 或 doc_id，需要新建画板 | lark-cli docs +update --api-version v2 --doc <doc_id> --command append --content '<whiteboard type="blank"></whiteboard>' --as user，从响应 data.new_blocks[0].block_token 取得（block_type == "whiteboard" 的那条；参数详见 lark-doc SKILL.md） |
Step 2：渲染 & 写入
→ 进入 § 渲染 & 写入画板 章节，按流程完成后直接返回结果给用户。
修改 Workflow
Step 1：获取 board_token（同创作 Workflow Step 1）
What ships with it
27 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/connectors.md 5.5 KB
- references/content.md 1.5 KB
- references/image.md 4.3 KB
- references/lark-whiteboard-query.md 2.1 KB
- references/lark-whiteboard-update.md 3.6 KB
- references/layout.md 19 KB
- references/schema.md 15 KB
- references/style.md 11 KB
- references/typography.md 2.1 KB
- routes/dsl.md 6.6 KB
- routes/mermaid.md 1.1 KB
- routes/svg.md 3.5 KB
- scenes/architecture.md 22 KB
- scenes/bar-chart.md 7.8 KB
- scenes/comparison.md 7.4 KB
- scenes/fishbone.md 9.6 KB
- scenes/flowchart.md 11 KB
- scenes/flywheel.md 8.6 KB
- scenes/funnel.md 4.2 KB
- scenes/line-chart.md 9.4 KB
- scenes/mermaid.md 3.4 KB
- scenes/milestone.md 4.0 KB
- scenes/organization.md 8.2 KB
- scenes/photo-showcase.md 6.0 KB
- scenes/pyramid.md 3.9 KB
- scenes/swimlane.md 20 KB
- scenes/treemap.md 6.3 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 · 145 lines · 194 tokens per session scan A d7e6a5f48795
lark-whiteboard is a skill published in the GitHub repository yokingma/weclaws (38 stars, last pushed 3mo ago), licensed MIT. It adds 194 tokens to every session and 2,135 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to lark-whiteboard, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
frontend-design
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
dxf
Generate, regenerate, and validate 2D DXF drawings from Python build123d sources. Use for DXF files, .py drawing scripts, @dxf models, 2D profiles, outlines, templates, gaskets, panels, flat patterns, laser/plasma/waterjet cut layouts, and 2D drawing exports of CAD geometry.
wxjava-api-contributor
A contributor guide for adding or maintaining official WeChat API support in WxJava, a Java software development kit. It covers services, request and response data objects, data conversion, HTTP handling, starter configuration, and regression tests.
wxjava-upgrade-guide
A migration guide for upgrading WxJava, a Java software development kit for WeChat services, from one version or dependency setup to another. It checks dependencies, Java versions, configuration, HTTP clients, and public programming interfaces.
frontend-ui-dark-ts
Build dark-themed React applications using Tailwind CSS with custom theming, glassmorphism effects, and Framer Motion animations. Use when creating dashboards, admin panels, or data-rich interfaces with a refined dark aesthetic.
last30Days
Resolve "last30Days" to a concrete ISO date range relative to your run time — a rolling 30-day window ending today. Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a "last 30 days" / trailing-month task…