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 agentmods add skills/larksuite/cli/lark-sharednpx skills add larksuite/cli --skill lark-sharedgit clone --depth 1 https://github.com/larksuite/cliWhat 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 | $0.00049 | $0.01165 |
| Opus 5 | $0.00024 | $0.00583 |
| Sonnet 5 | $0.00010 | $0.00233 |
| Haiku 4.5 | $0.00005 | $0.00117 |
Grade A, and why
lark-shared 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lark-cli 共享规则
所有 lark-* skill 共享的底座：身份、认证、输出契约与高风险操作。
通用准则
-
调用前先确认用法：执行前读对应 reference 或跑
--help，别猜 flag 盲调。 -
身份决定你代表谁操作：
--as user代表用户本人（能看到、也能操作其日历、云空间/云盘/云存储等个人资源），--as bot代表应用自己，应用级操作，只能访问bot自己的资源，bot 查用户资源会返回空成功而非报错。动手前先搞清楚身份identity。身份模型和权限管理 →lark-shared-identity-and-permissions.md。 -
授权 / 配置类 URL 必须配二维码：当命令输出
verification_url、verification_uri_complete、console_url等 URL 字段时，必须用lark-cli auth qrcode生成并在回复中展示，URL 在前二维码在后；优先生成 PNG（--output），仅当用户明确要求时才使用 ASCII（--ascii）。URL 原样转发——不编解码、不加标点、不重拼 query，二维码和链接请一起展示给用户。 -
--format json（默认）下，判断成功用ok == true（或进程退出码 0），不要用code == 0：成功信封没有顶层code/msg字段，code只出现在错误信封的error内。按 OpenAPI 老格式{"code": 0, "msg": "ok"}判断会把所有成功调用误判为失败——封装写入类命令时尤其危险。JSON 输出契约 →lark-shared-output-contract.md。
安全规则
-
禁止输出密钥（appSecret、accessToken等）到终端明文。
-
写入/删除操作前必须确认用户意图。
-
目标命令支持
--dry-run时，用--dry-run预览危险请求。 -
退出码 10 是高风险确认门禁（
risk: "high-risk-write"），不是错误：停下 → 向用户确认（展示action、risk和关键参数）→ 取得用户显式同意后，将hint指出的确认 flag 追加到你原始 argv 的末尾后重试；绝不静默加确认 flag 绕过 →lark-shared-high-risk-approval.md。 -
文件路径只接受相对路径：
--file、--output、--output-dir、@file等路径参数只接受 cwd 下的相对路径，传绝对路径会报unsafe file path。数据输入（@file、大 JSON）优先用 stdin 传入，避免路径和转义问题。
Reference 强触发索引
命中任一触发条件时，MUST 在执行下一步前读取对应 reference。命中多条时按表中顺序读取，同一reference只读取一次。
| 强触发条件（命中任一即必读） | Reference |
|---|---|
查看自己是谁(user/bot)、获取当前身份详细字段信息、身份诊断、--as选择逻辑、身份延续、登录态、认证、scope、授权和权限管理、missing_scopes 或 console_url、Agent 准备发起或完成 auth login |
lark-shared-identity-and-permissions.md |
| 需要依赖 JSON 输出契约判断成功 / 失败、读取 stdout / stderr，或为命令编写脚本与封装 | lark-shared-output-contract.md |
准备执行high-risk-write(高风险操作)、判断命令风险等级、遇到退出码 exit 10、confirmation_required、确认后重试 |
lark-shared-high-risk-approval.md |
首次使用CLI需运行 lark-cli config init 完成应用配置、或 CLI 明确提示 config init --new |
lark-shared-config-init.md |
用户询问 notice、CLI版本更新、或输出含 _notice（升级 / skills 落后 / 废弃命令提示） |
lark-shared-update-notice.md |
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.
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.
- 2d ago First seen · 49 lines · 49 tokens per session scan A 9fa68bb1f3ce
lark-shared is a skill published in the GitHub repository larksuite/cli (16,925 stars, last pushed today), licensed MIT. It adds 49 tokens to every session and 1,165 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.