Cross-reference restaurant recommendations from Xiaohongshu (小红书) and Dianping (大众点评) to validate restaurant quality and consistency. Use when querying restaurant recommendations by geographic location (city/district) to get validated insights from both platforms. Automatically fetches ratings, review counts, and analyzes consistency across platforms to provide trustworthy recommendations with confidence scores.
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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 restaurant-crosscheckOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install restaurant-crosscheck⚠️ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js →
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/restaurant-crosscheck/💡Extract and place the folder at the path above, then restart your agent.
Category
Developer & DevOpsWhat Restaurant recommendation cross-validation can do for your AI workflow
Cross-reference restaurant directly from your Claude conversation
Works across Claude, Cursor, OpenClaw — install once, use everywhere
Trusted by 1,119+ developers worldwide
One-command installation — no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Restaurant recommendation cross-validation
Help me get started with Restaurant recommendation cross-validation
Explains what Restaurant recommendation cross-validation does, walks through the setup, and runs a quick demo based on your current project
Use Restaurant recommendation cross-validation to cross-reference restaurant recommendations from Xiaohongshu (小红书) a...
Invokes Restaurant recommendation cross-validation with the right parameters and returns the result directly in the conversation
What can I do with Restaurant recommendation cross-validation in my developer & devops workflow?
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Restaurant recommendation cross-validation extends your AI assistant with the ability to cross-reference restaurant recommendations from Xiaohongshu (小红书) and Dianping (大众点评) to validate restaurant quality and consistency. Use when querying restaurant recommendations by geographic location (city/district) to get validated insights from both platforms. Automatically fetches ratings, review counts, and analyzes consistency across platforms to provide trustworthy recommendations with confidence scores. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly — and it will take care of the task end-to-end, using Restaurant recommendation cross-validation as its underlying capability.
Restaurant recommendation cross-validation works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) — an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Restaurant recommendation cross-validation 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 Restaurant recommendation cross-validation, copy the skill folder to `~/.claude/skills/restaurant-crosscheck/` for use across all your projects, or `.claude/skills/restaurant-crosscheck/` for a single project. Restart Claude and the skill is immediately active — invoke it with `/restaurant-crosscheck` or just describe your goal and the AI will pick it up automatically.
Restaurant recommendation cross-validation has been installed 1,119 times, making it one of the more actively used skills in the Developer & DevOps category. The install rate suggests it solves a real, recurring need rather than a niche edge case. 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/restaurant-crosscheck/ for personal use (all projects), or .claude/skills/restaurant-crosscheck/ for project-specific use. Restart your AI client, then invoke with /restaurant-crosscheck or let the AI discover it automatically.
Restaurant recommendation cross-validation supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Restaurant recommendation cross-validation is free to install. Check the repository for licensing information.
Cross-reference restaurant recommendations from Xiaohongshu (小红书) and Dianping (大众点评) to validate restaurant quality and consistency. Use when querying restaurant recommendations by geographic location (city/district) to get validated insights from both platforms. Automatically fetches ratings, review counts, and analyzes consistency across platforms to provide trustworthy recommendations with confidence scores.
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Platforms
Lists the top use cases for Restaurant recommendation cross-validation, with example commands for each scenario
Automate my developer & devops tasks using Restaurant recommendation cross-validation
Identifies repetitive steps in your workflow and sets up Restaurant recommendation cross-validation to handle them automatically
Restaurant recommendation cross-validation is categorized under Developer & DevOps. These skills help AI agents perform specialized tasks in this domain.
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