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钉钉/飞书集成 - 企业通讯、机器人、自动化工作流（Slack 中国版）
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Use when the user wants academic literature search, paper discovery, citation graph lookup, PubMed or Google Scholar retrieval, arXiv or Rxiv preprint search, or AI4Scholar-powered citation insertion inside Codex. Prefer the bundled script over generic web search when the user explicitly wants AI4Scholar.
Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Academic literature review workflow for research topic selection. Use when user asks to do literature survey, research topic exploration, or systematic review for a specific field. Triggers include: "literature review for [field]", "research topic selection", "help me design a search strategy", "systematic literature search", or when user describes a multi-step research workflow involving database searching, relevance assessment, journal filtering, and topic analysis.
Use this skill when the user wants to work with Google NotebookLM from Codex through the `notebooklm-py` CLI, including logging in, listing notebooks, selecting a notebook, adding sources, asking questions, exporting metadata, or generating NotebookLM artifacts.
| name | dingtalk-feishu-cn |
| description | 钉钉/飞书集成 - 企业通讯、机器人、自动化工作流（Slack 中国版） |
| metadata | {"openclaw":{"emoji":"💼","category":"productivity","tags":["dingtalk","feishu","lark","china","enterprise","slack"]}} |
企业通讯、机器人、自动化工作流。
| 功能 | 钉钉 | 飞书/Lark |
|---|---|---|
| Webhook | ✅ | ✅ |
| API | ✅ | ✅ |
| 机器人 | ✅ | ✅ |
| 文档 | ✅ | ✅✅ |
| 国际化 | ❌ | ✅ |
# 发送消息
curl -X POST "https://oapi.dingtalk.com/robot/send?access_token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"msgtype": "text",
"text": {"content": "这是一条测试消息"}
}'
# 使用 dingtalk-sdk
pip install dingtalk-sdk
from dingtalk import SecretClient
client = SecretClient(APP_KEY, APP_SECRET)
# 发送消息
curl -X POST "https://open.feishu.cn/open-apis/bot/v2/hook/YOUR_HOOK" \
-H "Content-Type: application/json" \
-d '{
"msg_type": "text",
"content": {"text": "这是一条测试消息"}
}'
# 使用 lark-oapi
pip install lark-oapi
import lark_oapi as lark
client = lark.Client.builder() \
.app_id(APP_ID) \
.app_secret(APP_SECRET) \
.build()
# 钉钉机器人
./scripts/dingtalk-notify.sh "告警: CPU 使用率 90%"
# 飞书机器人
./scripts/feishu-notify.sh "任务完成: 数据同步成功"
版本: 1.0.0