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 appleweiping/WEIPING_WIKI --skill lark-docgit clone --depth 1 https://github.com/appleweiping/WEIPING_WIKIWrote 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/appleweiping/weiping_wiki/lark-doc)<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-doc"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-doc.svg" alt="Measured on agentmods" 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 | $0.00219 | $0.02177 |
| Opus 5 | $0.00110 | $0.01089 |
| Sonnet 5 | $0.00044 | $0.00435 |
| Haiku 4.5 | $0.00022 | $0.00218 |
Grade A, and why
lark-doc 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 4d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
docs (v2)
⚠️ API 版本:本 skill 使用 v2 API。所有
docs +create --api-version v2、docs +fetch --api-version v2、docs +update --api-version v2命令必须携带--api-version v2。
# 常用示例
lark-cli docs +fetch --api-version v2 --doc "文档URL或token"
lark-cli docs +create --api-version v2 --content '<title>标题</title><p>内容</p>'
lark-cli docs +update --api-version v2 --doc "文档URL或token" --command append --content '<p>内容</p>'
前置条件 — 执行操作前必读
CRITICAL — 执行对应操作前,MUST 先用 Read 工具读取以下文件,缺一不可:
../lark-shared/SKILL.md— 认证、权限处理、全局参数(所有操作通用)- 读取文档(
docs +fetch --api-version v2) → 必读lark-doc-fetch.md(--scope/--detail选择、局部读取策略、<fragment>/<excerpt>输出结构) - 创建或编辑文档内容 → 必读
lark-doc-xml.md(XML 语法规则,仅当用户明确要求 Markdown 时改读lark-doc-md.md);从零创建时加读lark-doc-create-workflow.md;编辑已有文档时加读lark-doc-update-workflow.md
未读完以上文件就执行相应操作会导致参数选择错误、格式错误或样式不达标。
格式选择规则(全局):
- 创建 / 导入场景(
docs +create,或docs +update --command append/overwrite的整段写入):XML 和 Markdown 都可以。用户提供.md本地文件、或明确说"导入 Markdown"时,直接用 Markdown;否则默认 XML(可用 callout、grid、checkbox 等富 block)。- 精准编辑场景(
docs +update的str_replace/block_insert_after/block_replace/block_delete/block_move_after等局部精修指令):优先使用 XML(--doc-format xml,即默认值)。XML 能稳定表达 block 结构和样式,局部精修更可控;不要因为 Markdown 更简单就自行切换。
快速决策
- 用户需要在文档内创建、复制或移动资源块(画板、电子表格、多维表格等)时,必须先读取
lark-doc-xml.md的「三、资源块」章节 - 写文档时,重要信息(核心流程、架构、对比、风险、路线图、关键指标、因果关系)优先规划为画板,不要只用文字或表格承载
- 新增画板必须隔离到 SubAgent:简单图由 SubAgent 直接插入
<whiteboard type="svg">完整 SVG</whiteboard>,不读lark-whiteboard;复杂图才由主 Agent 先建<whiteboard type="blank"></whiteboard>,再启动 SubAgent 读取lark-whiteboard写入 - 用户说"看一下文档里的图片/附件/素材""预览素材" → 用
lark-cli docs +media-preview - 用户明确说"下载素材" → 用
lark-cli docs +media-download - 如果目标是画板/whiteboard/画板缩略图 → 只能用
lark-cli docs +media-download --type whiteboard(不要用+media-preview) - 用户说"找一个表格""按名称搜电子表格""找报表""最近打开的表格""最近我编辑过的 xxx" → 直接用
lark-cli drive +search(参考lark-drive)。老的docs +search已进入维护期、后续会下线,不要再新增依赖。 drive +search结果里会直接返回SHEET/Base/FOLDER等云空间对象,是资源发现的统一入口- 拿到 spreadsheet URL/token 后 → 切到
lark-sheets做对象内部操作 - 用户说"给文档加评论""查看评论""回复评论""给评论加/删除表情 reaction" → 切到
lark-drive处理 - 文档内容中出现嵌入的
<sheet>、<bitable>或<cite file-type="sheets|bitable">标签时 → 必须主动提取 token 并切到对应技能下钻读取内部数据,不能只呈现标签本身
What ships with it
13 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-doc-create.md 5.3 KB
- references/lark-doc-fetch.md 8.4 KB
- references/lark-doc-md.md 5.0 KB
- references/lark-doc-media-download.md 2.1 KB
- references/lark-doc-media-insert.md 6.8 KB
- references/lark-doc-media-preview.md 1.6 KB
- references/lark-doc-search.md 14 KB
- references/lark-doc-update.md 12 KB
- references/lark-doc-whiteboard.md 5.0 KB
- references/lark-doc-xml.md 8.1 KB
- references/style/lark-doc-create-workflow.md 3.6 KB
- references/style/lark-doc-style.md 6.7 KB
- references/style/lark-doc-update-workflow.md 4.6 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.
- 4d ago First seen · 70 lines · 219 tokens per session scan A 43a4e9e2e4d5
lark-doc is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 12d ago), licensed MIT. It adds 219 tokens to every session and 2,177 once invoked, about $0.0011 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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