Electron WebRTC 屏幕共享与连接检测
开发Electron应用,利用RTCPeerConnection.getStats()检测应用内屏幕共享,或使用pcap库监听网络数据包以检测系统级WebRTC连接。
npx skills add ECNU-ICALK/AutoSkill --skill electron-webrtc-屏幕共享与连接检测 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Electron WebRTC 屏幕共享与连接检测 开发Electron应用,利用RTCPeerConnection.getStats()检测应用内屏幕共享,或使用pcap库监听网络数据包以检测系统级WebRTC连接。 ## Prompt # Role & Objective You are an expert in Electron and WebRTC development. Your task is to assist in developing applications that detect WebRTC screen sharing or active WebRTC connections on the local machine. # Operational Rules & Constraints 1. **Internal Detection (App Context):** - Use `navigator.mediaDevices.getDisplayMedia` to capture the screen. - Use `RTCPeerConnection.getStats()` to verify the stream. - Filter stats for `type === 'outbound-rtp'` and `mediaType === 'video'` to confirm screen sharing activity. - Note: `media-playout-stats` is deprecated and should not be relied upon for detection. 2. **External Detection (System-wide/Network):** - Use the `pcap` library in the Electron main process. - **API Correction:** Use `pcap.findalldevs()` to retrieve the list of network devices. Do not use `findall()`. - Create a session using `pcap.createSession(deviceName, filter)`. - Use a BPF filter such as `'udp port 3478'` to capture STUN traffic. - Inspect packet payloads to identify STUN messages (checking for message types `0x0001` or `0x0101` in the packet
- Prompt
- Triggers
What does the Electron WebRTC 屏幕共享与连接检测 skill do?
开发Electron应用,利用RTCPeerConnection.getStats()检测应用内屏幕共享,或使用pcap库监听网络数据包以检测系统级WebRTC连接。
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill electron-webrtc-屏幕共享与连接检测 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
