Go CLI tool that instantly creates a public web terminal using ttyd and Cloudflare tunnels. Share your shell in seconds with optional password protection.
git clone https://github.com/STRRL/shell-now.gitShell Now is a lightweight Go CLI that turns your local terminal into a publicly accessible web shell in seconds using ttyd and Cloudflare Quick Tunnels. It automatically downloads and configures all dependencies across platforms, eliminating setup friction. The tool supports optional password authentication and can run any shell or custom command like htop or bash. Ideal for developers needing quick remote debugging, educators delivering live Linux demos, and teams sharing terminal sessions without complex infrastructure. Simply run one command to get a shareable public URL.
Install via Homebrew (brew tap strrl/collective && brew install shell-now), Docker, or direct download. Run shell-now to launch a web terminal with an auto-generated public URL. Optionally set a password for authentication. Share the URL with others to grant browser-based terminal access.
Live debugging: demonstrate terminal issues to teammates in real time
Remote education: teach Linux or DevOps concepts via browser in live sessions
CLI tool demos: share terminal-based application walkthroughs
Remote device access: connect to Pi or NAS without configuring public IP
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/STRRL/shell-nowCopy the install command above and run it in your terminal.
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Use the prompt template or examples below to test the skill.
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I want to share my terminal session with you. Here's the command I'm running: [COMMAND]. Can you help me troubleshoot or optimize it?
# Terminal Session Analysis ## Current Command ```bash [COMMAND] ``` ## Analysis - The command appears to be processing [DATA_TYPE] data from [SOURCE] - Potential optimization: Consider adding `--parallel` flag to speed up processing - Memory usage could be reduced by adding `--limit [MEMORY_LIMIT]` ## Recommendations 1. Try running with these optimizations: ```bash [COMMAND] --parallel --limit 2G ``` 2. Monitor memory usage with `htop` during execution 3. Consider breaking large datasets into smaller chunks for processing
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