lark-wiki

lark-wiki is a skill for Codex from appleweiping/WEIPING_WIKI. It costs 81 tokens per session (1,951 once invoked), scanned A, original, MIT.

A knowledge-base management tool for Feishu, also known as Lark, a collaboration platform with shared documents and wikis. It manages knowledge spaces, members, document nodes, hierarchy, and shortcuts.

In plain words
What is it for?
Use it to find or create documents, browse wiki structures, manage space members, and move or copy nodes.
Why use it?
It helps organize shared company documentation and perform common knowledge-base administration tasks.

Skill for Codex

Written for Codex: installed under .codex/.

Good fit Use it to find or create documents, browse wiki structures, manage space members, and move or copy nodes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/appleweiping/weiping_wiki/lark-wiki
Install

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.

Any agent
npx skills add appleweiping/WEIPING_WIKI --skill lark-wiki
Clone the repo
git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI

Made for: Codex.

Wrote 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.

agentmods badge for lark-wiki

README.md
[![agentmods](https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-wiki/github.svg)](https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-wiki)
Your own site
<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-wiki"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-wiki/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.

agentmods 80×15 button for lark-wiki

Your own site · 80×15
<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-wiki"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-wiki.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,951 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00081 $0.01951
Opus 5 $0.00041 $0.00975
Sonnet 5 $0.00016 $0.00390
Haiku 4.5 $0.00008 $0.00195

Measured 6d ago against content hash 10010c3134b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

lark-wiki 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 6d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.codex/skills/lark-wiki/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 members create 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

快速决策

  • 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)。
  • 用户要在知识库中创建新节点,优先使用 lark-cli wiki +node-create
  • 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”三类之一,再决定 member_type,不要先调 wiki members create 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 members create --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 + 添加成员”:先解析对应 ID,再执行 wiki members create

成员添加流程

  • 调用 lark-cli wiki members create 前,先把自然语言里的“人 / 群 / 部门”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
  • 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 members create。对于部门场景,这意味着必须是 --as user

Read the full file on GitHub · 107 lines

Files

What ships with it

6 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.

Changes

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.

  1. 6d ago First seen · 107 lines · 81 tokens per session scan A 10010c3134b0

Subscribe to this mod's changes

lark-wiki is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 15d ago), licensed MIT. It adds 81 tokens to every session and 1,951 once invoked, about $0.0004 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.