Screen Monitor
v1.0.1Dual-mode screen sharing and analysis. Model-agnostic (Gemini/Claude/Qwen3-VL).
⭐ 4· 4.7k·28 current·30 all-time
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
The skill name/description (screen sharing + vision analysis) aligns with the included files: a local WebRTC web page, a small Node.js backend storing frames, and helper scripts to capture and analyze screenshots. The browser-extension path for deeper control is consistent with the stated 'full control' mode.
Instruction Scope
Runtime instructions call the included scripts which (a) read Clawdbot config (references/env-check.sh), (b) may take OS screenshots (screen-analyze.sh uses 'import' or 'screencapture'), and (c) invoke 'clawdbot agent' to analyze images. Those actions go beyond simply serving a sharing page and grant access to local files, system capture tools, and agent config. The skill does not declare or warn about reading the agent config or taking OS screenshots in all cases.
Install Mechanism
No install spec (instruction-only) reduces installation risk, but the package includes executable scripts and a Node.js backend file that a user can run. There is no automated installer, so risk depends on how the agent/platform executes these files; the presence of a Node server implies the agent or user will run node on the host.
Credentials
The skill declares no required environment variables or external credentials, which is proportionate. However, the env-check.sh script reads Clawdbot configuration (clawdbot config get skills.screen-monitor.visionUrl) and will attempt to curl a vision endpoint (default http://localhost:8080). Accessing local agent config and calling local network endpoints is not declared in manifest fields and should be considered by users.
Persistence & Privilege
The skill is not always-enabled and does not request elevated platform privileges. It does run a local server on port 18795 and writes frames to /tmp, which persist locally until removed. Autonomous model invocation remains the platform default — combine that with the ability to take OS screenshots and run 'clawdbot agent' and you get a larger blast radius if the skill is invoked without careful user consent.
What to consider before installing
This skill appears to implement what it claims, but please consider these risks before installing or running it:
- Local server exposure: The backend sets Access-Control-Allow-Origin: '*' and serves on LAN IP/port 18795 by default. If you expose that port to your LAN, other LAN users (or malware on your network) could submit frames or interact with the endpoint without authentication. Prefer binding the server to localhost only or adding an authentication token.
- Unauthenticated frame storage: Captured frames are written to /tmp/clawdbot-screen-latest.png (and metadata to /tmp). These files can be read by other local users/processes. If you have sensitive on-screen content, don't run this on a shared machine.
- OS screenshots & system commands: The screen-analyze.sh script can invoke OS-level screenshot tools and will call 'clawdbot agent' to analyze images. Make sure you trust the skill source before letting it take screenshots or access the agent runtime.
- Config and network access: env-check.sh reads Clawdbot configuration and may contact a vision model endpoint (default localhost:8080). Verify that this behavior is acceptable and that no sensitive endpoints will be queried or leaked.
- Mitigations if you want to try it: run it on an isolated machine or VM, modify backend-endpoint.js to listen on 127.0.0.1 only and remove CORS '*', add simple token-based auth for /api/screen-frame, ensure /tmp files are removed after use and have restrictive permissions, and inspect/host the code yourself rather than fetching unknown builds. If you don't trust the author/repository, avoid installing it on machines with sensitive data.
Given the lack of documented authentication and the fact this skill can capture and persist screen images, treat it as potentially sensitive and proceed only with the above safeguards.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
Runtime requirements
🖥️ Clawdis
