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-contactgit 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-contact)<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-contact"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-contact/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/appleweiping/weiping_wiki/lark-contact"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-contact.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00139 | $0.00730 |
| Opus 5 | $0.00069 | $0.00365 |
| Sonnet 5 | $0.00028 | $0.00146 |
| Haiku 4.5 | $0.00014 | $0.00073 |
Grade A, and why
lark-contact 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- lark-contact — 91% identical, 1 lines differ
- lark-contact — 91% identical, 1 lines differ
What it actually says
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
# 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
- 发消息 / 查聊天记录 →
lark-im - 排日程 / 邀请会议 →
lark-calendar - 部门树 / 按部门列员工 / 组织架构 ,通过
lark-openapi-explorer查找原生接口
What ships with it
2 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.
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.
- 6d ago First seen · 45 lines · 139 tokens per session scan A 1661770d3ee6
lark-contact is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 15d ago), licensed MIT. It adds 139 tokens to every session and 730 once invoked, about $0.0007 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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