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 fanfan-de/anybox --skill lark-whiteboardgit clone --depth 1 https://github.com/fanfan-de/anyboxWrote 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/fanfan-de/anybox/lark-whiteboard)<a href="https://agentmods.dev/skills/fanfan-de/anybox/lark-whiteboard"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/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/fanfan-de/anybox/lark-whiteboard"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/lark-whiteboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 32 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 34 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 35 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 103 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 36 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 37 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00119 | $0.02153 |
| Opus 5 | $0.00060 | $0.01077 |
| Sonnet 5 | $0.00024 | $0.00431 |
| Haiku 4.5 | $0.00012 | $0.00215 |
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 9d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
whiteboard (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
核心概念
画板 Token
画板 token 是画板的唯一标识符。飞书画板嵌入在云文档中，可以从云文档的 docs +fetch 结果中获取（<whiteboard token="xxx"/>
标签），或从 docs +update 新建画板后的 data.board_tokens 字段中获取。
快速决策
当需要插入图表时：
- 能否使用飞书画板？
- 能 → 走画板路径（推荐！可编辑、可协作）
- 不能 → 走图片路径
| 用户需求 | 推荐 Shortcut |
|---|---|
| "查看这个画板的内容" | +query --output_as image |
| "导出画板为图片" | +query --output_as image |
| "获取画板的 PlantUML/Mermaid 代码" | +query --output_as code |
| "检查画板是否由 PlantUML/Mermaid 代码块组成" | +query --output_as code |
| "修改画板某个节点的颜色或文字" | +query --output_as raw 后 +update |
| "用 PlantUML 绘制画板" | +update --input_format plantuml |
| "用 Mermaid 绘制画板" | +update --input_format mermaid |
| "在画板绘制复杂图表" | +update --input_format raw, 需要使用 whiteboard-cli 工具，参见 lark-whiteboard-cli |
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 7.6 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.
- 9d ago First seen · 119 lines · 119 tokens per session scan A fa4ad6d3c8c6
lark-whiteboard is a skill published in the GitHub repository fanfan-de/anybox (57 stars, last pushed 1mo ago), licensed MIT. It adds 119 tokens to every session and 2,153 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 2026-09-03.
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