google-agents-cli-eval
Evaluate ADK agents with metrics, evalsets, and the iterative eval-fix loop.
lark-openapi-explorer
Discover and call native Lark OpenAPI endpoints from official documentation when existing skills fall short.
Full skill instructions
前置条件: 先阅读
../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。
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。
严格按以下步骤逐层检索,不要跳步或猜测 API:
# 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。
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"
open.feishu.cnopen.larksuite.com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"
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"
使用 lark-cli api 裸调:
# 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>
向用户呈现挖掘结果时,按以下格式组织:
METHOD /open-apis/...lark-cli api 的完整命令如果用户使用英文交流,将以上所有内容翻译为英文。
--dry-run 预览请求(如支持)# 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"}'
# 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>"]}'
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