Agent skill

Lark Contact

by appleweiping in appleweiping/WEIPING_WIKI

飞书 / Lark 通讯录,用于按姓名 / 邮箱把员工解析成 openid,以及按 openid 反查员工的姓名 / 部门 / 邮箱 / 联系方式。当用户说出某人姓名而下一步需要发消息 / 加群 / 排日程时,先用本 skill 把姓名换成 ID;当输出里出现 openid 需要展示成姓名给用户看,或用户直接询问某人的部门 / 邮箱 / 联系方式时,用本 skill…

MITAuto-check passedProductivity & Automation

Install Lark Contact

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

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

GitHub CLI
$ gh skill install appleweiping/WEIPING_WIKI lark-contact --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-contact .claude/skills/lark-contact && 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-contact
GitHub stars
119
Token cost
~403 tokens
SKILL.md length
74 words
Files
3 (incl. references)
Skills in repo
51
Repo updated
First seen
Licence
MIT

At a glance

飞书 / Lark 通讯录,用于按姓名 / 邮箱把员工解析成 openid,以及按 openid 反查员工的姓名 / 部门 / 邮箱 / 联系方式。当用户说出某人姓名而下一步需要发消息 / 加群 / 排日程时,先用本 skill 把姓名换成 ID;当输出里出现 openid 需要展示成姓名给用户看,或用户直接询问某人的部门 / 邮箱 / 联系方式时,用本 skill…

  • Tasks that involve Messaging and chat bots
  • SKILL.md covers 选哪个命令, 典型场景, 注意事项 and 不在本 skill 范围
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve OpenAPI specifications

What it does

Lark Contact is an agent skill from appleweiping/WEIPING_WIKI. 飞书 / Lark 通讯录,用于按姓名 / 邮箱把员工解析成 openid,以及按 openid 反查员工的姓名 / 部门 / 邮箱 / 联系方式。当用户说出某人姓名而下一步需要发消息 / 加群 / 排日程时,先用本 skill 把姓名换成 ID;当输出里出现 openid 需要展示成姓名给用户看,或用户直接询问某人的部门 / 邮箱 / 联系方式时,用本 skill 查。不负责部门树遍历、按部门列员工、组织架构图,这类需求走原生 OpenAPI。

Its SKILL.md is about 400 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/lark-contact-get-user.md` and `references/lark-contact-search-user.md`).

It sits in Productivity & Automation, covering Messaging and chat bots and OpenAPI specifications. It works with 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 OpenAPI specifications

Example prompts

  • “/lark-contact”

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

    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 Contact loads about 403 tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 74 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~403
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.9k

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). 74 words, ~403 tokens.

Download SKILL.mdSave it as .claude/skills/lark-contact/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
lark-contact
description
飞书 / Lark 通讯录,用于按姓名 / 邮箱把员工解析成 open_id,以及按 open_id 反查员工的姓名 / 部门 / 邮箱 / 联系方式。当用户说出某人姓名而下一步需要发消息 / 加群 / 排日程时,先用本 skill 把姓名换成 ID;当输出里出现 open_id 需要展示成姓名给用户看,或用户直接询问某人的部门 / 邮箱 / 联系方式时,用本 skill 查。不负责部门树遍历、按部门列员工、组织架构图,这类需求走原生 OpenAPI。
metadata.cliHelp
lark-cli contact --help

lark-contact

选哪个命令

user 身份和 bot 身份是两条完全独立的路径。先确定当前身份,再按下表选命令:

想做什么user 身份bot 身份
按姓名 / 邮箱搜员工拿 open_id+search-user不支持
已知 open_id 取他人资料+search-user --user-ids <id>+get-user --user-id <id>
查看自己+get-user 或 +search-user --user-ids me不支持

已知 open_id 只是想发消息 / 排日程,不必经过 contact —— 直接 lark-im / lark-calendar。

典型场景

bash
# 找张三给他发消息:先搜,确认 open_id,再发
lark-cli contact +search-user --query "张三" --has-chatted --as user
lark-cli im +messages-send --user-id ou_xxx --text "Hi!"

搜索命中多条且后续操作有副作用(发消息、邀请会议等),把候选列给用户挑;不要擅自选第一条。

注意事项

  • 41050 / Permission denied 受当前身份的可见范围限制(两条命令都可能遇到)。换 bot 身份或让管理员调整可见范围,细节见 lark-shared。
  • 跨租户用户(is_cross_tenant=true)多数业务字段为空字符串,这是飞书可见性规则,下游做空值兜底。
  • ID 类型:默认 open_id。+get-user 可改 --user-id-type union_id|user_id;+search-user 只接受 open_id。

不在本 skill 范围

© 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 2 other files (references) in skill/lark-contact of appleweiping/WEIPING_WIKI.

  • SKILL.md
  • references/lark-contact-get-user.md
  • references/lark-contact-search-user.md

Open the folder on GitHubat commit 76fdc42

Compare with similar skills

Lark Contact 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 Contact compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Lark Contact this skillappleweiping/WEIPING_WIKI119—~403Automated safety check: PassMIT
Lark Contactrongxinzy/RongxinAI1542 repos~479Automated safety check: PassAGPL-3.0
Feishu Openapi Skillholon-run/uxc116—~2.3kAutomated safety check: PassMIT
Feishucodewhale-hq/Codewhale41k—~413Automated safety check: PassMIT
Jacred Tracker Parserjacred-fdb/jacred126—~1.4kAutomated safety check: PassAGPL-3.0
SpecfusionLiangNiang/OpenMantis110—~2.1kAutomated safety check: NotesApache-2.0

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Works with

Questions about Lark Contact

What does Lark Contact do?

飞书 / Lark 通讯录,用于按姓名 / 邮箱把员工解析成 openid,以及按 openid 反查员工的姓名 / 部门 / 邮箱 / 联系方式。当用户说出某人姓名而下一步需要发消息 / 加群 / 排日程时,先用本 skill 把姓名换成 ID;当输出里出现 openid 需要展示成姓名给用户看,或用户直接询问某人的部门 / 邮箱 / 联系方式时,用本 skill…. Lark Contact is an agent skill from appleweiping/WEIPING_WIKI.

When should I use Lark Contact?

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

How do I install Lark Contact in Claude Code?

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

How do I install Lark Contact in Codex?

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

Can I use Lark Contact 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-contact -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-contact, .gemini/skills/lark-contact, .github/skills/lark-contact and .opencode/skills/lark-contact in your project.

What does Lark Contact need to run?

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

Does Lark Contact 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 Contact 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 Contact use?

Lark Contact 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 Contact use?

About 403 tokens (SKILL.md is roughly 1.6k 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 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Lark Contact?

Skills that share tags, products or a category with Lark Contact: Lark Contact (rongxinzy/RongxinAI, 154 stars), Feishu Openapi Skill (holon-run/uxc, 116 stars), Feishu (codewhale-hq/Codewhale, 41k stars) and Jacred Tracker Parser (jacred-fdb/jacred, 126 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lark Contact?

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.