OpenClaw Lark/Feishu Plugin connects an OpenClaw agent to Lark or Feishu workspaces, allowing it to work with messages, documents, databases, spreadsheets, calendars, and tasks. It is for OpenClaw users who want their agent to read and update Lark/Feishu workspace data. The catalogue skills provide the agent workflows for operating those connected workspace features.
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 larksuite/openclaw-lark --skill feishu-fetch-docgit clone --depth 1 https://github.com/larksuite/openclaw-larkWrote 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/larksuite/openclaw-lark/feishu-fetch-doc)<a href="https://agentmods.dev/skills/larksuite/openclaw-lark/feishu-fetch-doc"><img src="https://agentmods.dev/badge/skills/larksuite/openclaw-lark/feishu-fetch-doc/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/larksuite/openclaw-lark/feishu-fetch-doc"><img src="https://agentmods.dev/badge/skills/larksuite/openclaw-lark/feishu-fetch-doc.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 | $0.00042 | $0.00902 |
| Opus 5 | $0.00021 | $0.00451 |
| Sonnet 5 | $0.00008 | $0.00180 |
| Haiku 4.5 | $0.00004 | $0.00090 |
Grade A, and why
feishu-fetch-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 11d 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
94% identical to feishu-fetch-doc — 11 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
feishu_mcp_fetch_doc
获取飞书云文档的 Markdown 内容（Lark-flavored 格式）。
重要：图片、文件、画板的处理
文档中的图片、文件、画板需要通过 feishu_doc_media（action: download）工具单独获取！
识别格式
返回的 Markdown 中，媒体文件以 HTML 标签形式出现：
-
图片：
<image token="Z1FjxxxxxxxxxxxxxxxxxxxtnAc" width="1833" height="2491" align="center"/> -
文件：
<view type="1"> <file token="Z1FjxxxxxxxxxxxxxxxxxxxtnAc" name="skills.zip"/> </view> -
画板：
<whiteboard token="Z1FjxxxxxxxxxxxxxxxxxxxtnAc"/>
获取步骤
- 从 HTML 标签中提取
token属性值 - 调用
feishu_doc_media下载：{ "action": "download", "resource_token": "提取的token", "resource_type": "media", "output_path": "/path/to/save/file" }
参数
doc_id（必填）：支持直接传文档 URL 或 token- 直接传 URL：
https://xxx.feishu.cn/docx/Z1FjxxxxxxxxxxxxxxxxxxxtnAc（系统自动提取 token） - 直接传 token：
Z1FjxxxxxxxxxxxxxxxxxxxtnAc - 知识库 URL/token 也支持：
https://xxx.feishu.cn/wiki/Z1FjxxxxxxxxxxxxxxxxxxxtnAc或Z1FjxxxxxxxxxxxxxxxxxxxtnAc
- 直接传 URL：
Wiki URL 处理策略
知识库链接（/wiki/TOKEN）背后可能是云文档、电子表格、多维表格等不同类型的文档。当不确定类型时, 不能直接假设是云文档，必须先查询实际类型。
处理流程
- 先调用
feishu_wiki_space_node（action: get）解析 wiki token：{ "action": "get", "token": "wiki_token_here" } - 从返回的
node中获取obj_type（实际文档类型）和obj_token（实际文档 token） - 根据
obj_type调用对应工具：
| obj_type | 工具 | 传参 |
|---|---|---|
docx |
feishu_mcp_fetch_doc |
doc_id = obj_token |
sheet |
feishu_sheet |
spreadsheet_token = obj_token |
bitable |
feishu_bitable_* 系列 |
app_token = obj_token |
| 其他 | 告知用户暂不支持该类型 | — |
示例
用户：帮我看下这个文档 https://xxx.feishu.cn/wiki/ABC123
- 调用
feishu_wiki_space_node（action: get, token: ABC123） - 返回
obj_type: "docx",obj_token: "doxcnXYZ789" - 调用
feishu_mcp_fetch_doc（doc_id: doxcnXYZ789）
工具组合
| 需求 | 工具 |
|---|---|
| 获取文档文本 | feishu_mcp_fetch_doc |
| 下载图片/文件/画板 | feishu_doc_media（action: download） |
| 解析 wiki token 类型 | feishu_wiki_space_node（action: get） |
| 读写电子表格 | feishu_sheet |
| 操作多维表格 | feishu_bitable_* 系列 |
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.
- 11d ago First seen · 94 lines · 42 tokens per session scan A 5c43b2045f07
feishu-fetch-doc is a skill published in the GitHub repository larksuite/openclaw-lark (2,375 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 902 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to feishu-fetch-doc, differing in 11 lines, and is treated as a copy.
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