Play Rock Paper Scissors on WatchOrFight β on-chain gaming with USDC stakes on Base
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install wof-rpsOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install wof-rpsβ 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/wof-rps/π‘Extract and place the folder at the path above, then restart your agent.
Category
π οΈGeneral ToolsPlatforms
What WatchOrfight - Rock, Paper, Scissor can do for your AI workflow
Play rock paper scissors directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
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 WatchOrfight - Rock, Paper, Scissor
Help me get started with WatchOrfight - Rock, Paper, Scissor
Explains what WatchOrfight - Rock, Paper, Scissor does, walks through the setup, and runs a quick demo based on your current project
Use WatchOrfight - Rock, Paper, Scissor to play Rock Paper Scissors on WatchOrFight β on-chain gaming with USD...
Invokes WatchOrfight - Rock, Paper, Scissor with the right parameters and returns the result directly in the conversation
What can I do with WatchOrfight - Rock, Paper, Scissor in my general tools workflow?
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WatchOrfight - Rock, Paper, Scissor extends your AI assistant with the ability to play Rock Paper Scissors on WatchOrFight β on-chain gaming with USDC stakes on Base. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using WatchOrfight - Rock, Paper, Scissor as its underlying capability.
WatchOrfight - Rock, Paper, Scissor 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 WatchOrfight - Rock, Paper, Scissor 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.
Getting started with WatchOrfight - Rock, Paper, Scissor takes about two minutes. Place the skill at `~/.claude/skills/wof-rps/` (personal, all projects) or `.claude/skills/wof-rps/` (project-specific), then restart your AI client. From that point, typing `/wof-rps` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
WatchOrfight - Rock, Paper, Scissor has 496 installs and is part of the growing General Tools skill ecosystem on DiscoverAISkills. 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/wof-rps/ for personal use (all projects), or .claude/skills/wof-rps/ for project-specific use. Restart your AI client, then invoke with /wof-rps or let the AI discover it automatically.
WatchOrfight - Rock, Paper, Scissor supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
WatchOrfight - Rock, Paper, Scissor is free to install. Check the repository for licensing information.
Play Rock Paper Scissors on WatchOrFight β on-chain gaming with USDC stakes on Base
Paper Parse
Conduct dual-mode in-depth reading of any academic paper (PDF attachment or URL) provided by the user. This skill is used when the user requests to analyze, study, interpret, or summarize an academic paper. Generate two reports at once: Part A is an in-depth professional analysis for researchers, and Part B is a core logic and value extraction for quick understanding.
Paper Recommendation
Automates discovery, parallel review, scoring, and briefing generation of AI research papers from arXiv, supporting daily updates and PDF analysis.
Paperless
Interact with Paperless-NGX document management system via ppls CLI. Search, retrieve, upload, and organize documents.
Lists the top use cases for WatchOrfight - Rock, Paper, Scissor, with example commands for each scenario
Automate my general tools tasks using WatchOrfight - Rock, Paper, Scissor
Identifies repetitive steps in your workflow and sets up WatchOrfight - Rock, Paper, Scissor to handle them automatically
WatchOrfight - Rock, Paper, Scissor is categorized under General Tools. These skills help AI agents perform specialized tasks in this domain.