AI-powered LuLu Firewall companion for macOS. Monitors firewall alerts, analyzes connections with AI, sends Telegram notifications with Allow/Block buttons....
Data sourced from ClawHub. View on ClawSkills
Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install lulu-monitorOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install lulu-monitorβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/lulu-monitor/π‘Extract and place the folder at the path above, then restart your agent.
Category
π¬CommunicationPlatforms
What LuLu Monitor can do for your AI workflow
Ai-powered lulu firewall directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 1,482+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing LuLu Monitor
Send a Slack message to the #engineering channel about the deployment
Formats and sends the message with relevant context, tagging the right people
Summarize all unread messages in my inbox from today
Reads messages across connected channels and returns a prioritized summary
Draft a reply to this customer complaint and send it for review
Writes an empathetic, professional response and routes it to the approval queue
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Staying on top of communications across multiple channels is a real challenge for modern teams. LuLu Monitor helps by enabling ai-powered lulu firewall companion for macos. monitors firewall alerts, analyzes connections with ai, sends telegram notifications with allow/block buttons... directly from your AI assistant, without switching apps or logging into separate platforms.
LuLu Monitor works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install LuLu Monitor once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
To install LuLu Monitor, copy the skill folder to `~/.claude/skills/lulu-monitor/` for use across all your projects, or `.claude/skills/lulu-monitor/` for a single project. Restart Claude and the skill is immediately active β invoke it with `/lulu-monitor` or just describe your goal and the AI will pick it up automatically.
LuLu Monitor has been installed 1,482 times, making it one of the more actively used skills in the Communication category. The install rate suggests it solves a real, recurring need rather than a niche edge case. The source code is open on GitHub β you can inspect it, contribute fixes, or fork it to adapt the skill for your specific setup. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/lulu-monitor/ for personal use (all projects), or .claude/skills/lulu-monitor/ for project-specific use. Restart your AI client, then invoke with /lulu-monitor or let the AI discover it automatically.
LuLu Monitor supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
LuLu Monitor is free to install. Check the repository for licensing information.
AI-powered LuLu Firewall companion for macOS. Monitors firewall alerts, analyzes connections with AI, sends Telegram notifications with Allow/Block buttons....
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Links
LuLu Monitor is categorized under Communication. These skills help AI agents perform specialized tasks in this domain.
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