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Agent skill

Lark Wiki

by rongxinzy in rongxinzy/RongxinAI

飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是…

AGPL-3.0Auto-check passedProductivity & Automation

Install Lark Wiki

skills CLI
$ npx skills add rongxinzy/RongxinAI --skill lark-wiki -a claude-code

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

GitHub CLI
$ gh skill install rongxinzy/RongxinAI lark-wiki --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/rongxinzy/RongxinAI.git skills-src && mkdir -p .claude/skills && cp -r skills-src/MCPs/feishu/skills/lark-wiki .claude/skills/lark-wiki && 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-wiki
GitHub stars
154
Used in
3 other repos
Token cost
~1.9k tokens
SKILL.md length
567 words
Files
14 (incl. references)
Skills in repo
94
Repo updated
First seen
Licence
AGPL-3.0

At a glance

飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是…

  • Tasks that involve Messaging and chat bots
  • SKILL.md covers 身份选择：优先使用 user 身份, 快速决策, Shortcuts（推荐优先使用） and 成员添加流程, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Lark Wiki is an agent skill from rongxinzy/RongxinAI. 飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是 URL 路径模式和 token，而不是域名。不负责：上传文件到知识库节点下（走 lark-drive）、编辑文档/表格/Base 内容（走 lark-doc / lark-sheets / lark-base）。

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including reference files (for example `references/lark-wiki-delete-space.md`, `references/lark-wiki-member-add.md` and `references/lark-wiki-member-list.md`).

It sits in Productivity & Automation, covering Messaging and chat bots. The repository describes itself as: An all-in-one local AI Agent workspace with a fully self-developed stack. The licence is AGPL-3.0.

When your agent uses it

  • Tasks that involve Messaging and chat bots

Example prompts

  • “/lark-wiki”

What it can do on your machine

Read from SKILL.md and the folder at commit 9c64865. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

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

  • Network

    No URLs in SKILL.md.

    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 Wiki loads about 1.9k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 567 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~16k

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 rongxinzy/RongxinAI at commit 9c64865, republished under its AGPL-3.0 licence (© rongxinzy). 567 words, ~1,882 tokens.

Download SKILL.mdSave it as .claude/skills/lark-wiki/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
lark-wiki
description
飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是 URL 路径模式和 token，而不是域名。不负责：上传文件到知识库节点下（走 lark-drive）、编辑文档/表格/Base 内容（走 lark-doc / lark-sheets / lark-base）。
version
1.0.3
metadata.cliHelp
lark-cli wiki --help

wiki (v2)

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

成员管理硬限制：

  • 如果目标是“部门”，先判断身份，再决定是否继续。
  • --as bot 对应 tenant_access_token。官方限制：这种身份下不能使用部门 ID (opendepartmentid) 添加知识空间成员。
  • 遇到“部门 + --as bot”时，禁止先调用 lark-cli wiki +member-add 试错；直接说明该路径不可行。
  • 如果用户明确要求“以 bot 身份运行”，且目标是部门，必须停下说明 bot 路径无法完成，不要静默切到 --as user。

身份选择：优先使用 user 身份

知识空间和节点都是用户的个人资源，策略上应优先显式使用 --as user（CLI 的 --as 默认值为 auto，不带 --as 时常被解析成 bot，列出的是应用所属空间而非用户的）。仅当用户明确要求“应用 / bot 视角”时才用 --as bot（仍受上面的成员管理硬限制约束）。

快速决策

  • 用户要按特定主题 / 关键词 / 内容线索查找资料并收集到知识库节点或新建知识库节点下，必须先阅读 ../lark-drive/references/lark-drive-workflow.md，再按其中 Workflow Registry 进入 topic_move_collector workflow。该 workflow 使用 Drive 全量搜索召回，再按 Wiki 目标解析、确认和移动；不要只用 Wiki 节点列表做局部遍历。
  • 用户要整理 / 盘点 / 归类 / 重构知识库、个人文档库、文档库目录或 Wiki 节点结构，或要生成整理方案、目标目录树、移动计划时，不要只使用 Wiki 节点 API。必须先阅读 ../lark-drive/references/lark-drive-workflow.md，再按其中 Workflow Registry 进入 knowledge_organize workflow；该 workflow 负责 Drive / Wiki / 个人文档库的统一入口解析、资源盘点、分类计划、写前确认和结果验证。
  • 用户要把已有 Wiki 节点移出知识库，放到 Drive 文件夹或“我的空间”根目录：使用 wiki +move-to-drive，不要使用 wiki +move 或 drive +move。这是会改变节点归属和权限继承的写操作，执行前确认源节点与目标位置。
  • 用户给的是知识库 URL（.../wiki/<token>），且后续要查成员/加成员/删成员：先调用 lark-cli wiki spaces get_node --params '{"token":"<wiki_token>"}' 获取 space_id，后续成员接口统一使用 space_id。
  • 用户要删除知识空间（wiki +delete-space）但只给了名称或 URL：不能把名称 / URL 原样传给 --space-id，必须先解析出真实 space_id。解析方式：
    • URL（.../wiki/<token>）：lark-cli wiki spaces get_node --params '{"token":"<wiki_token>"}' --format json，读 data.node.space_id。
    • 只知名称：lark-cli wiki spaces list --format json，边翻页边收集 items 并按 name 精确匹配；一旦任一页累计到至少 1 条精确匹配就停止翻页。只有当翻完所有页（has_more=false）仍无精确匹配时，才对已收集的全量 items 做宽松匹配（name trim 空格、大小写不敏感、子串包含）。
    • 关键安全约束：无论精确还是模糊，无论命中 1 条还是多条，发起删除前都必须把候选（name + space_id + description + space_type）列给用户，由用户明确选定一个 space_id 再执行。不要因为"只命中一条"就自动执行删除。
    • 命中 0 条：停下来问用户是名称拼错了还是调用方无权限；不要自行改名字重试。
    • 用户明确选定后再执行 lark-cli wiki +delete-space --space-id <ID> --yes（高风险写操作，必须显式 --yes）。
    • 反例：不要把 wiki URL / 名称直接当 --space-id（如 --space-id "https://.../wiki/<wiki_token>"）；务必先用 wiki spaces get_node 解析出 data.node.space_id 再传。
  • 用户要在知识库中创建新节点，优先使用 lark-cli wiki +node-create。
  • 用户要列出 Wiki 节点：先用 wiki +space-list --as user 拿数字 space_id，再用 wiki +node-list --space-id <space_id>。不要把 wiki URL、node token、doc token、名称直接当 --space-id。钻子节点时 --parent-node-token 必须是 wiki node token；如果用户给的是 docx/sheet/base URL，先用 wiki +node-get --node-token <url> 解析出 node_token。
  • wiki +node-list 命中 invalid_parameters、not_found、permission_denied 时，不要重复调用同一参数；按 hint 修 space_id / parent_node_token / 权限。只有 rate_limit 才做退避重试。
  • 用户说“给知识库添加成员/管理员”：先把目标解析成“用户 / 群 / 部门 / 应用”四类之一，再决定 --member-type，不要先调 wiki +member-add 再根据报错反推类型。
  • 用户说“部门 + bot”：这是已知不支持路径。不要继续尝试 wiki +member-add --as bot；直接提示必须改成 --as user，或明确告知当前要求无法完成。
  • 用户说“用户 / 群 / 应用 + 添加成员”：先解析对应 ID，再执行 wiki +member-add。
  • 用户说“查看 / 列出空间成员”：用 wiki +member-list；该 shortcut 默认只取一页，多成员场景显式加 --page-all。
  • 用户说“移除 / 删除空间成员”：用 wiki +member-remove，必须传齐原始授予时的 --member-type 和 --member-role（不知道就先 wiki +member-list 查一下）。

Shortcuts（推荐优先使用）

Shortcut 是对常用操作的高级封装（lark-cli wiki +<verb> [flags]）。有 Shortcut 的操作优先使用。

Shortcut说明
+moveMove a wiki node, or move a Drive document into Wiki
+move-to-driveMove a wiki node to a Drive folder and poll the async task
+node-createCreate a wiki node with automatic space resolution
+delete-spaceDelete a wiki space, polling the async delete task when needed
+space-listList all wiki spaces accessible to the caller
+space-createCreate a wiki space (user identity only)
+node-listList wiki nodes in a space or under a parent node (supports pagination)
+node-copyCopy a wiki node to a target space or parent node
+node-getGet a wiki node's details by node_token / obj_token / Lark URL
+node-deleteDelete a wiki node, polling the async delete task when needed
+member-addAdd a member to a wiki space
+member-removeRemove a member from a wiki space
+member-listList members of a wiki space (supports pagination)
Show full SKILL.md (158 more words)Show less

成员添加流程

  • 调用 lark-cli wiki +member-add 前，先把自然语言里的“人 / 群 / 部门 / 应用”解析成正确的 --member-id，不要猜格式。
  • 用户场景默认优先 --member-type=openid：用 lark-cli contact +search-user --query "<姓名/邮箱/手机号>" --format json 获取 open_id。
  • 群组场景使用 --member-type=openchat：用 lark-cli im +chat-search --query "<群名关键词>" --format json 获取 chat_id。
  • 应用场景使用 --member-type=appid：--member-id 传应用 ID，格式通常为 cli_xxx。
  • userid / unionid 只在下游明确要求时才使用；先拿到 open_id，再调用 lark-cli api GET /open-apis/contact/v3/users/<open_id> --params '{"user_id_type":"open_id"}' --format json 读取 user_id / union_id。
  • 部门场景使用 --member-type=opendepartmentid：当前 CLI 没有 shortcut，需调用 lark-cli api POST /open-apis/contact/v3/departments/search --as user --params '{"department_id_type":"open_department_id"}' --data '{"query":"<部门名>"}' 获取 open_department_id。
  • 只有在目标类型和身份都已确认可行后，才调用 lark-cli wiki +member-add。对于部门场景，这意味着必须是 --as user。

目标语义约束

  • 我的文档库 / My Document Library / 我的知识库 / 个人知识库 / my_library 都应视为 Wiki personal library，不是 Drive 根目录
  • 处理这类目标时，先解析 my_library 对应的真实 space_id，再执行 wiki +move、wiki +node-create 或其他 Wiki 写操作
  • 不要因为缺少显式 space_id 就退化成 drive +move
  • 如果用户明确说的是 Drive 文件夹、云空间（云盘/云存储）根目录、我的空间，再按源对象分流：源对象是 Wiki 节点时用 wiki +move-to-drive，源对象已在 Drive 时用 drive +move

API Resources

bash
lark-cli schema wiki.<resource>.<method>   # 调用原生 API 前必须先查看 --data / --params 参数结构，不要猜测字段格式
lark-cli wiki <resource> <method> [flags]  # 调用 API
spaces
  • create — 创建知识空间
  • get — 获取知识空间信息
  • get_node — 获取知识空间节点信息
  • list — 获取知识空间列表
members
  • create — 添加知识空间成员
  • delete — 删除知识空间成员
  • list — 获取知识空间成员列表
nodes
  • copy — 创建知识空间节点副本
  • create — 创建知识空间节点
  • list — 获取知识空间子节点列表

不在本 skill 范围

  • 上传 / 下载文件到知识库节点下 → lark-drive（drive +upload --wiki-token）
  • 编辑文档正文内容 → lark-doc
  • 表格 / 多维表格数据操作 → lark-sheets / lark-base
  • 按名称搜索文档 / Wiki / 表格文件、评论与权限管理 → lark-drive

© rongxinzy, AGPL-3.0. 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 13 other files (references) in MCPs/feishu/skills/lark-wiki of rongxinzy/RongxinAI.

  • SKILL.md
  • references/lark-wiki-delete-space.md
  • references/lark-wiki-member-add.md
  • references/lark-wiki-member-list.md
  • references/lark-wiki-member-remove.md
  • references/lark-wiki-move-to-drive.md
  • references/lark-wiki-move.md
  • references/lark-wiki-node-copy.md
  • references/lark-wiki-node-create.md
  • references/lark-wiki-node-delete.md
  • references/lark-wiki-node-get.md
  • references/lark-wiki-node-list.md
  • references/lark-wiki-space-create.md
  • references/lark-wiki-space-list.md

Open the folder on GitHubat commit 9c64865

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in rongxinzy/RongxinAI, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Lark Wiki 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 Wiki compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Lark Wiki this skillrongxinzy/RongxinAI1543 repos~1.9kAutomated safety check: PassAGPL-3.0
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She Love Me863401402/she-love-me9311 repos~1.3kAutomated safety check: PassMIT
Feishu Docraucvr/Group-Goki1123 repos~592Automated safety check: PassMIT
Wechat Article Extractorfreestylefly/wechat-article-extractor-skill1361 repos~1kAutomated safety check: PassNone
Wechat Miniprogram Builderchenjin-cmd/wechat-miniprogram-builder356—~634Automated safety check: PassMIT

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Categories

Questions about Lark Wiki

What does Lark Wiki do?

飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是…. Lark Wiki is an agent skill from rongxinzy/RongxinAI.

When should I use Lark Wiki?

Lark Wiki fits situations like: tasks that involve Messaging and chat bots.

How do I install Lark Wiki in Claude Code?

Run `npx skills add rongxinzy/RongxinAI --skill lark-wiki -a claude-code`. Or copy the skill folder (MCPs/feishu/skills/lark-wiki in rongxinzy/RongxinAI) into .claude/skills/lark-wiki in your project. Claude Code loads it when a task matches its description.

How do I install Lark Wiki in Codex?

Run `npx skills add rongxinzy/RongxinAI --skill lark-wiki -a codex`. Or copy the skill folder (MCPs/feishu/skills/lark-wiki in rongxinzy/RongxinAI) into .agents/skills/lark-wiki in your project. Codex loads it when a task matches its description.

Can I use Lark Wiki 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 rongxinzy/RongxinAI --skill lark-wiki -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-wiki, .gemini/skills/lark-wiki, .github/skills/lark-wiki and .opencode/skills/lark-wiki in your project.

What does Lark Wiki need to run?

SKILL.md names no scripts, command-line tools or credentials: Lark Wiki is instructions for the agent only.

Does Lark Wiki access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Lark Wiki 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 Wiki use?

Lark Wiki is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lark Wiki use?

About 1.9k tokens (SKILL.md is roughly 7.5k 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 14k tokens, read only when the agent opens those files.

What are the alternatives to Lark Wiki?

Skills that share tags, products or a category with Lark Wiki: Feishu Doc (openclaw/openclaw, 392k stars), She Love Me (863401402/she-love-me, 931 stars), Feishu Doc (raucvr/Group-Goki, 112 stars) and Wechat Article Extractor (freestylefly/wechat-article-extractor-skill, 136 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lark Wiki?

rongxinzy (a GitHub organization) maintains it in rongxinzy/RongxinAI, which has 154 GitHub stars. The repository holds 94 skills in this directory. The repository was last updated on October 10, 2026.

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