Find and execute cross-chain arbitrage opportunities. Scans prices across all chains, evaluates profitability after all costs (gas, bridge fees, slippage), assesses risk, and executes if profitable. Uses ERC-7683 for cross-chain settlement. Supports scan-only mode for research without execution.
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 cross-chain-arbitrageOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install cross-chain-arbitrageβ 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/cross-chain-arbitrage/π‘Extract and place the folder at the path above, then restart your agent.
Category
π£Marketing & GrowthWhat Uniswap Cross Chain Arbitrage can do for your AI workflow
Cross-chain arbitrage 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 Uniswap Cross Chain Arbitrage
Help me get started with Uniswap Cross Chain Arbitrage
Explains what Uniswap Cross Chain Arbitrage does, walks through the setup, and runs a quick demo based on your current project
Use Uniswap Cross Chain Arbitrage to find and execute cross-chain arbitrage opportunities
Invokes Uniswap Cross Chain Arbitrage with the right parameters and returns the result directly in the conversation
What can I do with Uniswap Cross Chain Arbitrage in my marketing & growth workflow?
Lists the top use cases for Uniswap Cross Chain Arbitrage, with example commands for each scenario
Guides & tutorials for AI skills
The 7 AI Skills Every Software Developer Should Have Installed in 2026
After testing dozens of developer-focused AI skills, these are the seven that have proven genuinely useful across different tech stacks and workflows β not just impressive demos, but tools that hold up under daily use.
MCP Skills vs Native Claude Tools: What's the Difference and When to Use Each
Claude comes with built-in capabilities, but MCP skills extend it in ways the base model can't. Here's a clear breakdown of what each type of tool is good for, with real examples of when to reach for a skill versus relying on Claude's native abilities.
Uniswap Cross Chain Arbitrage extends your AI assistant with the ability to find and execute cross-chain arbitrage opportunities. Scans prices across all chains, evaluates profitability after all costs (gas, bridge fees, slippage), assesses risk, and executes if profitable. Uses ERC-7683 for cross-chain settlement. Supports scan-only mode for research without execution. 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 Uniswap Cross Chain Arbitrage as its underlying capability.
Uniswap Cross Chain Arbitrage 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 Uniswap Cross Chain Arbitrage 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 Uniswap Cross Chain Arbitrage, copy the skill folder to `~/.claude/skills/cross-chain-arbitrage/` for use across all your projects, or `.claude/skills/cross-chain-arbitrage/` for a single project. Restart Claude and the skill is immediately active β invoke it with `/cross-chain-arbitrage` or just describe your goal and the AI will pick it up automatically.
Uniswap Cross Chain Arbitrage has 972 installs and is part of the growing Marketing & Growth 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/cross-chain-arbitrage/ for personal use (all projects), or .claude/skills/cross-chain-arbitrage/ for project-specific use. Restart your AI client, then invoke with /cross-chain-arbitrage or let the AI discover it automatically.
Uniswap Cross Chain Arbitrage supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Uniswap Cross Chain Arbitrage is free to install. Check the repository for licensing information.
Find and execute cross-chain arbitrage opportunities. Scans prices across all chains, evaluates profitability after all costs (gas, bridge fees, slippage), assesses risk, and executes if profitable. Uses ERC-7683 for cross-chain settlement. Supports scan-only mode for research without execution.
Cross-Pollination Engine
Systematically borrow ideas from unrelated industries to solve problems. Innovation often comes from adjacent fields. Use when user says "cross-pollination", "how would X solve this", "borrow ideas from", "what can we learn from", "think outside the box", "how would Disney/Apple/Amazon do this", "different industry", "steal ideas".
Help other OpenClaw instances achieve memory synchronization through GitHub repository
Automatically synchronize OpenClaw memory files through GitHub private repository to achieve two-way updating and conflict handling of data between multiple devices.
Chain of Density
Platforms
Automate my marketing & growth tasks using Uniswap Cross Chain Arbitrage
Identifies repetitive steps in your workflow and sets up Uniswap Cross Chain Arbitrage to handle them automatically
Uniswap Cross Chain Arbitrage is categorized under Marketing & Growth. These skills help AI agents perform specialized tasks in this domain.
Iteratively densify text summaries using Chain-of-Density technique. Use when compressing verbose documentation, condensing requirements, or creating executive summaries while preserving information density.