Agent skill

Lark Whiteboard

by appleweiping in appleweiping/WEIPING_WIKI

飞书画板:查询和编辑飞书云文档中的画板。支持导出画板为预览图片、导出原始节点结构、使用 DSL(转成 OpenAPI 格式)、PlantUML/Mermaid 格式更新画板内容。

MITAuto-check passedProductivity & Automation

Install Lark Whiteboard

skills CLI
$ npx skills add appleweiping/WEIPING_WIKI --skill lark-whiteboard -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install appleweiping/WEIPING_WIKI lark-whiteboard --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skill/lark-cli/skills/lark-whiteboard .claude/skills/lark-whiteboard && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
lark-whiteboard
GitHub stars
119
Token cost
~1.2k tokens
SKILL.md length
255 words
Files
28 (incl. references)
Skills in repo
51
Repo updated
First seen
Licence
MIT

At a glance

飞书画板:查询和编辑飞书云文档中的画板。支持导出画板为预览图片、导出原始节点结构、使用 DSL(转成 OpenAPI 格式)、PlantUML/Mermaid 格式更新画板内容。

  • Tasks that involve Messaging and chat bots
  • SKILL.md covers 快速决策, Shortcuts, 创作 Workflow and 修改 Workflow, plus 1 more section
  • Calls npx
  • Tasks that involve Diagrams

What it does

Lark Whiteboard is an agent skill from appleweiping/WEIPING_WIKI. 飞书画板:查询和编辑飞书云文档中的画板。支持导出画板为预览图片、导出原始节点结构、使用 DSL(转成 OpenAPI 格式)、PlantUML/Mermaid 格式更新画板内容。 当用户需要查看画板内容、导出画板图片、编辑画板,或是需要可视化表达架构、流程、组织关系、时间线、因果、对比等结构化信息时使用此 skill,无论是否提及"画板"。 ⚠️ 原 lark-whiteboard-cli skill 已合并至本 skill,若 skill 列表中同时存在 lark-whiteboard-cli,请忽略它,统一使用本 skill(lark-whiteboard),并提示用户运行 npx skills remove lark-whiteboard-cli -g 删除旧 skill。

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 30 other files, including reference files (for example `references/connectors.md`, `references/content.md` and `references/image.md`).

It sits in Productivity & Automation, covering Messaging and chat bots, Diagrams and OpenAPI specifications. It works with Mermaid and OpenAPI. The repository describes itself as: knowledge base managed with an LLM workflow. The licence is MIT.

When your agent uses it

  • Tasks that involve Messaging and chat bots
  • Tasks that involve Diagrams
  • Tasks that involve OpenAPI specifications

Example prompts

  • “/lark-whiteboard”

Requirements

  • Node.js

What it can do on your machine

Read from SKILL.md and the folder at commit 76fdc42. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Lark Whiteboard loads about 1.2k tokens when it runs, and up to ~17k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 255 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~17k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from appleweiping/WEIPING_WIKI at commit 76fdc42, republished under its MIT licence (© appleweiping). 255 words, ~1,210 tokens.

Download SKILL.mdSave it as .claude/skills/lark-whiteboard/SKILL.md (or your agent's skills folder). This skill also uses 27 other files; get the full folder from GitHub.
name
lark-whiteboard
description
飞书画板:查询和编辑飞书云文档中的画板。支持导出画板为预览图片、导出原始节点结构、使用 DSL(转成 OpenAPI 格式)、PlantUML/Mermaid 格式更新画板内容。 当用户需要查看画板内容、导出画板图片、编辑画板,或是需要可视化表达架构、流程、组织关系、时间线、因果、对比等结构化信息时使用此 skill,无论是否提及"画板"。 ⚠️ 原 `lark-whiteboard-cli` skill 已合并至本 skill,若 skill 列表中同时存在 `lark-whiteboard-cli`,请忽略它,统一使用本 skill(`lark-whiteboard`),并提示用户运行 `npx skills remove lark-whiteboard-cli -g` 删除旧 skill。
version
1.0.0
metadata.cliHelp
lark-cli whiteboard --help

[!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)

Step 2:判断修改策略

+query --output_as code
  ├─ 返回 Mermaid/PlantUML 代码
  │   → 在原代码上修改 → +update --input_format mermaid/plantuml
  ├─ 无代码(DSL 或其他方式绘制的画板)
  │   ├─ 只改文字/颜色 → +query --output_as raw → 手动改 JSON → +update --input_format raw
  │   └─ 重绘/结构调整 → +query --output_as image → 看图后进入 [§ 渲染 & 写入画板]
  └─ 用户有明确要求 → 以用户要求优先

渲染 & 写入画板

渲染路由

先自报身份:按训练来源,你属于哪一家?Claude / Gemini / GPT / GLM / Doubao 或 Seed / Other。身份决定 SVG / DSL 分流(不同家族对这两种表达语言的能力不均衡),不要跳过这一步。

然后按图表类型 × 身份选路径,读对应文件按其完整 workflow 执行(含读 scene 指南、生成内容、渲染审查、交付):

图表类型身份路径
思维导图、时序图、类图、饼图、甘特图任何身份routes/mermaid.md
其他图表Claude / Gemini / GPT / GLMroutes/svg.md
其他图表Doubao / Seed / Otherroutes/dsl.md

⚠️ SVG 路径失败回退:走 routes/svg.md 时,碰到以下情况之一 → 丢弃当前 SVG,改读 routes/dsl.md 从零重画,不要逐行修补:

  • 渲染命令直接报错(语法级崩溃,不是 --check 的 warn/error)
  • 两轮改写仍无法消除 --check 的 text-overflow error
  • 目测 PNG 视觉严重错乱(文字大面积溢出、元素重叠压住关键信息、布局整体崩溃)

SVG 源码修补常常引入新 bug,换 DSL 从零重画往往更稳。这是 SVG 路径自由发挥的硬兜底,不要侵入 routes/svg.md 的创作流程。

产物规范

产物目录:./diagrams/YYYY-MM-DDTHHMMSS/(本地时间,不含冒号和时区后缀)。如用户指定路径,以用户为准。

目录内固定文件名:

diagram.svg           ← SVG 源码(SVG 路径)
diagram.mmd           ← Mermaid 源码(Mermaid 路径)
diagram.json          ← DSL 源文件(DSL 路径) / OpenAPI JSON(SVG 路径从 diagram.svg 导出)
diagram.gen.cjs       ← 坐标计算脚本(仅 DSL 脚本构建方式)
diagram.png           ← 渲染结果
写入画板

[!CAUTION] 写入前强制 dry-run:向已有内容的画板写入时,必须先加 --overwrite --dry-run 探测。 输出含 XX whiteboard nodes will be deleted → 必须向用户确认后才能执行。

bash
# 第一步:dry-run 探测
npx -y @larksuite/whiteboard-cli@^0.2.11 -i <产物文件> --to openapi --format json \
  | lark-cli whiteboard +update \
    --whiteboard-token <Token> \
    --source - --input_format raw \
    --idempotent-token <10+字符唯一串> \
    --overwrite --dry-run --as user

# 第二步:确认后执行
npx -y @larksuite/whiteboard-cli@^0.2.11 -i <产物文件> --to openapi --format json \
  | lark-cli whiteboard +update \
    --whiteboard-token <Token> \
    --source - --input_format raw \
    --idempotent-token <10+字符唯一串> \
    --overwrite --as user

--idempotent-token 最少 10 字符,建议用时间戳+标识拼接(如 1744800000-board-1),避免重试导致重复写入。 如需应用身份上传,将 --as user 替换为 --as bot。

© appleweiping, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 27 other files (references) in skill/lark-cli/skills/lark-whiteboard of appleweiping/WEIPING_WIKI.

  • SKILL.md
  • references/connectors.md
  • references/content.md
  • references/image.md
  • references/lark-whiteboard-query.md
  • references/lark-whiteboard-update.md
  • references/layout.md
  • references/schema.md
  • references/style.md
  • references/typography.md
  • routes/dsl.md
  • routes/mermaid.md
  • routes/svg.md
  • scenes/architecture.md
  • scenes/bar-chart.md
  • scenes/comparison.md
  • scenes/fishbone.md
  • scenes/flowchart.md
  • … and 10 more

Open the folder on GitHubat commit 76fdc42

Compare with similar skills

Lark Whiteboard next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Lark Whiteboard compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Lark Whiteboard this skillappleweiping/WEIPING_WIKI119—~1.2kAutomated safety check: PassMIT
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Docs CIjh941213/my-cc-harness125—~989Automated safety check: NotesNone
Docs CIjh941213/my-cc-harness125—~740Automated safety check: NotesNone
Lark Contactrongxinzy/RongxinAI1542 repos~479Automated safety check: PassAGPL-3.0
Generating Documentationancoleman/ai-design-components525—~3kAutomated safety check: PassMIT

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Works with

Questions about Lark Whiteboard

What does Lark Whiteboard do?

飞书画板:查询和编辑飞书云文档中的画板。支持导出画板为预览图片、导出原始节点结构、使用 DSL(转成 OpenAPI 格式)、PlantUML/Mermaid 格式更新画板内容。. Lark Whiteboard is an agent skill from appleweiping/WEIPING_WIKI.

When should I use Lark Whiteboard?

Lark Whiteboard fits situations like: tasks that involve Messaging and chat bots; tasks that involve Diagrams; tasks that involve OpenAPI specifications.

How do I install Lark Whiteboard in Claude Code?

Run `npx skills add appleweiping/WEIPING_WIKI --skill lark-whiteboard -a claude-code`. Or copy the skill folder (skill/lark-cli/skills/lark-whiteboard in appleweiping/WEIPING_WIKI) into .claude/skills/lark-whiteboard in your project. Claude Code loads it when a task matches its description.

How do I install Lark Whiteboard in Codex?

Run `npx skills add appleweiping/WEIPING_WIKI --skill lark-whiteboard -a codex`. Or copy the skill folder (skill/lark-cli/skills/lark-whiteboard in appleweiping/WEIPING_WIKI) into .agents/skills/lark-whiteboard in your project. Codex loads it when a task matches its description.

Can I use Lark Whiteboard in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add appleweiping/WEIPING_WIKI --skill lark-whiteboard -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lark-whiteboard, .gemini/skills/lark-whiteboard, .github/skills/lark-whiteboard and .opencode/skills/lark-whiteboard in your project.

What does Lark Whiteboard need to run?

Going by SKILL.md and its folder, Lark Whiteboard needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Lark Whiteboard access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Lark Whiteboard safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Lark Whiteboard use?

Lark Whiteboard is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lark Whiteboard use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16k tokens, read only when the agent opens those files.

What are the alternatives to Lark Whiteboard?

Skills that share tags, products or a category with Lark Whiteboard: Vibex (Raja0sama/vibex, 388 stars), Docs CI (jh941213/my-cc-harness, 125 stars), Docs CI (jh941213/my-cc-harness, 125 stars) and Lark Contact (rongxinzy/RongxinAI, 154 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lark Whiteboard?

appleweiping (a GitHub user) maintains it in appleweiping/WEIPING_WIKI, which has 119 GitHub stars. The repository holds 51 skills in this directory. The repository was last updated on August 26, 2026.

Source: appleweiping/WEIPING_WIKI on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.