Atlas / Skills / larksuite / Lark Openapi Explorer

Lark Openapi ExplorerSAFE

skills/larksuite/lark-openapi-explorer

The official Lark/飞书 CLI tool, maintained by the larksuite team — built for humans and AI Agents. Covers core business domains including Messenger, Docs, Base, Sheets, Calendar, Mail, Tasks, Meetings, and more, with 200+ commands and 20+ AI Agent Skills.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.0.0
Hosts
—
License
MIT
Stars
17,544
01

Overview

The official Lark/飞书 CLI tool, maintained by the larksuite team — built for humans and AI Agents. Covers core business domains including Messenger, Docs, Base, Sheets, Calendar, Mail, Tasks, Meetings, and more, with 200+ commands and 20+ AI Agent Skills.

Read from source at commit 91a26abd3925OBSERVED · 2026-10-07
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: lark-openapi-explorer
version: 1.0.0
description: "飞书/Lark 原生 OpenAPI 探索:从官方文档库中挖掘未经 CLI 封装的原生 OpenAPI 接口。当用户的需求无法被现有 lark-* skill 或 lark-cli 已注册命令满足,需要查找并调用原生飞书 OpenAPI 时使用。"
metadata:
  requires:
    bins: ["lark-cli"]
---

# OpenAPI Explorer

> **前置条件:** 先阅读 [`../lark-shared/SKILL.md`](../lark-shared/SKILL.md) 了解认证、身份切换和安全规则。

当用户的需求**无法被现有 skill 或 CLI 已注册 API 覆盖**时,使用本技能从飞书官方 markdown 文档库中逐层挖掘原生 OpenAPI 接口,然后通过 `lark-cli api` 裸调完成任务。

## 文档库结构

飞书 OpenAPI 文档以 markdown 层级组织:

```
llms.txt                          ← 顶层索引,列出所有模块文档链接
  └─ llms-<module>.txt            ← 模块文档,包含功能概述 + 底层 API 文档链接
       └─ <api-doc>.md            ← 单个 API 的完整说明(方法/路径/参数/响应/错误码)
```

文档入口:

| 品牌 | 入口 URL |
|------|----------|
| 飞书 (Feishu) | `https://open.feishu.cn/llms.txt` |
| Lark | `https://open.larksuite.com/llms.txt` |

> 所有文档以**中文**编写。如果用户使用英文交流,需将文档内容翻译为英文后输出。

## 挖掘流程

严格按以下步骤逐层检索,**不要跳步或猜测 API**:

### Step 1:确认现有能力不足

```bash
# 先检查是否已有对应的 skill 或已注册 API
lark-cli <可能的service> --help
```

如果已有对应命令或 shortcut,直接使用,**不需要继续挖掘**。

### Step 2:从顶层索引定位模块

用 WebFetch 获取顶层索引,找到与需求相关的模块文档链接:

```
WebFetch https://open.feishu.cn/llms.txt
  → 提取问题:"列出所有模块文档链接,找出与 <用户需求关键词> 相关的链接"
```

- 飞书品牌使用 `open.feishu.cn`
- Lark 品牌使用 `open.larksuite.com`
- 如不确定用户品牌,默认使用飞书

### Step 3:从模块文档定位具体 API

用 WebFetch 获取模块文档,找到具体 API 的文档链接:

```
WebFetch https://open.feishu.cn/llms-docs/zh-CN/llms-<module>.txt
  → 提取问题:"找出与 <用户需求> 相关的 API 说明和文档链接"
```

### Step 4:获取 API 完整规范

用 WebFetch 获取具体 API 文档,提取完整的调用规范:

```
WebFetch https://open.feishu.cn/document/server-docs/.../<api>.md
  → 提取问题:"返回完整 API 规范:HTTP 方法、URL 路径、路径参数、查询参数、请求体字段(名称/类型/必填/说明)、响应字段、所需权限、错误码"
```

### Step 5:通过 CLI 调用 API

使用 `lark-cli api` 裸调:

```bash
# GET 请求
lark-cli api GET /open-apis/<path> --params '{"key":"value"}'

# POST 请求
lark-cli api POST /open-apis/<path> --data '{"key":"value"}'

# PUT 请求
lark-cli api PUT /open-apis/<path> --data '{"key":"value"}'

# DELETE 请求
lark-cli api DELETE /open-apis/<path>
```

## 输出规范

向用户呈现挖掘结果时,按以下格式组织:

1. **API 名称与功能**:一句话描述
2. **HTTP 方法与路径**:`METHOD /open-apis/...`
3. **关键参数**:列出必填和常用可选参数
4. **所需权限**:scope 列表
5. **调用示例**:给出 `lark-cli api` 的完整命令
6. **注意事项**:频率限制、特殊约束等

如果用户使用英文交流,将以上所有内容翻译为英文。

## 安全规则

- **写入/删除类 API**(POST/PUT/DELETE)调用前必须确认用户意图
- 建议先用 `--dry-run` 预览请求(如支持)
- 不要猜测 API 路径或参数——必须从文档中获取确认
- 涉及敏感操作(删除群、移除成员等)时,向用户说明影响范围

## 使用场景示例

### 场景 1:用户需要拉人进群(未被 CLI 封装)

```bash
# Step 1: 确认 CLI 没有封装
lark-cli im --help
# → 发现没有 chat_members 相关的 create 命令

# Step 2-4: 通过文档挖掘获得 API 规范
# → POST /open-apis/im/v1/chats/:chat_id/members

# Step 5: 调用
lark-cli api POST /open-apis/im/v1/chats/oc_xxx/members \
  --data '{"id_list":["ou_xxx","ou_yyy"]}' \
  --params '{"member_id_type":"open_id"}'
```

### 场景 2:用户需要设置群公告

```bash
# Step 1: 确认 CLI 没有封装
lark-cli im --help
# → 没有 announcement 相关命令

# Step 2-4: 挖掘文档
# → PATCH /open-apis/im/v1/chats/:chat_id/announcement

# Step 5: 调用
lark-cli api PATCH /open-apis/im/v1/chats/oc_xxx/announcement \
  --data '{"revision":"0","requests":["<html>公告内容</html>"]}'
```

## 参考

- [lark-shared](../lark-shared/SKILL.md) — 认证和全局参数
- [lark-skill-maker](../lark-skill-maker/SKILL.md) — 如需将挖掘到的 API 固化为新 Skill
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-07 · audit v0.4.1 · source sha 91a26abd3925full audit observations/trust-audit/skill/larksuite__lark-openapi-explorer.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-0791a26abd3925SAFEB89first audit
05

Questions

What does the Lark Openapi Explorer skill do?

The official Lark/飞书 CLI tool, maintained by the larksuite team — built for humans and AI Agents. Covers core business domains including Messenger, Docs, Base, Sheets, Calendar, Mail, Tasks, Meetings, and more, with 200+ commands and 20+ AI Agent Skills.

Is Lark Openapi Explorer safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Lark Openapi Explorer access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (91a26abd3925), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.

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