jingsongliujing/feishu-cli-web/lark-skill-maker

Claude Code and agent skill by jingsongliujing/feishu-cli-web

Trust tier 2
  • community
LLM review pending
Source check pending

Checking that the SKILL.md file is still in the repository.

创建 lark-cli 的自定义 Skill。当用户需要把飞书 API 操作封装成可复用的 Skill(包装原子 API 或编排多步流程)时使用。

Install

npx vskill@latest install jingsongliujing/feishu-cli-web/lark-skill-maker

SKILL.md

The same SKILL.md was published earlier as larksuite/cli/lark-skill-maker.

Skill Maker

基于 lark-cli 创建新 Skill。Skill = 一份 SKILL.md,教 AI 用 CLI 命令完成任务。

CLI 核心能力

bash
lark-cli <service> <resource> <method> # 已注册 API
lark-cli <service> +<verb> # Shortcut(高级封装)
lark-cli api <METHOD> <path> [--data/--params] # 任意飞书 OpenAPI
lark-cli schema <service.resource.method> # 查参数定义

优先级:Shortcut > 已注册 API > api 裸调。

调研 API

bash
# 1. 查看已有的 API 资源和 Shortcut
lark-cli <service> --help
# 2. 查参数定义
lark-cli schema <service.resource.method>
# 3. 未注册的 API,用 api 直接调用
lark-cli api GET /open-apis/vc/v1/rooms --params '{"page_size":"50"}'
lark-cli api POST /open-apis/vc/v1/rooms/search --data '{"query":"5F"}'

如果以上命令无法覆盖需求(CLI 没有对应的已注册 API 或 Shortcut),使用 lark-openapi-explorer 从飞书官方文档库逐层挖掘原生 OpenAPI 接口,获取完整的方法、路径、参数和权限信息,再通过 lark-cli api 裸调完成任务。

通过以上流程确定需要哪些 API、参数和 scope。

SKILL.md 模板

文件放在 skills/lark-<name>/SKILL.md:

markdown
---
name: lark-<name>
version: 1.0.0
description: "<功能描述>。当用户需要<触发场景>时使用。"
metadata:
requires:
bins: ["lark-cli"]
---
# <标题>
> **前置条件:** 先阅读 [`../lark-shared/SKILL.md`](../lark-shared/SKILL.md)。
## 命令
\```bash
# 单步操作
lark-cli api POST /open-apis/xxx --data '{...}'
# 多步编排:说明步骤间数据传递
# Step 1: ...(记录返回的 xxx_id)
# Step 2: 使用 Step 1 的 xxx_id
\```
## 权限
| 操作 | 所需 scope |
|------|-----------|
| xxx | `scope:name` |

关键原则

  • description 决定触发 — 包含功能关键词 + "当用户需要...时使用"
  • 认证 — 说明所需 scope,登录用 lark-cli auth login --domain <name>
  • 安全 — 写入操作前确认用户意图,建议 --dry-run 预览
  • 编排 — 说明数据传递、失败回滚、可并行步骤

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
74
Repository forks
14
7-day trend score
22

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 2 Jul 2026, 4 months ago.

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