A powerful search integration for AI agents offering access to 17 global and domestic search engines without requiring API keys.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-search-engine1
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install multi-search-engine1 using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Multi Search Engine?
The Multi Search Engine skill is a comprehensive search integration designed for Openclaw Skills users who need deep web crawling capabilities. It supports 17 distinct engines, covering both Chinese domestic platforms like Baidu and WeChat, and international powerhouses like Google and DuckDuckGo. By utilizing direct URL patterns, this skill bypasses the need for complex API key management, allowing AI agents to perform real-time information retrieval across the surface and deep web seamlessly.\n\nThis skill is particularly effective for developers building research-heavy AI agents. It provides built-in support for advanced search operators, time-based filtering, and even specialized knowledge queries through WolframAlpha, making it a versatile tool for data gathering, competitive analysis, and automated research workflows.
Multi Search Engine Use Cases
- Performing cross-region market research using both domestic Chinese and international search engines.\n- Gathering time-sensitive data for news or trend analysis using specific time filters.\n- Conducting privacy-focused web crawling via DuckDuckGo and Startpage.\n- Automating document retrieval by searching for specific file types like PDFs or Excel sheets.\n- Executing complex mathematical or financial calculations through WolframAlpha integration.
How Multi Search Engine Works
- The AI agent selects the most appropriate search engine based on the query language and target region.\n2. A search URL is constructed using the specified keyword and optional advanced operators like site: or filetype:.\n3. The agent executes a web_fetch command to retrieve the search results page directly.\n4. Advanced filters, such as time parameters (tbs=qdr), are appended to refine results for accuracy.\n5. The retrieved data is processed and utilized for further agent actions or research summaries.
Multi Search Engine Setup
To implement this within your Openclaw Skills environment, ensure your agent has access to the web_fetch tool. No external API keys are required. You can test basic connectivity using the following command:\n\nbash\n# Example of a basic search query via web_fetch\nweb_fetch({\"url\": \"https://www.google.com/search?q=openclaw+skills\"})\n\n\nRefer to the internal documentation in references/ for detailed engine-specific configurations.
Multi Search Engine Data Schema & Taxonomy
The skill organizes its data through structured URL parameters and handles results based on the search engine's response format.\n\n| Engine Type | Key Engines | Primary Metadata Fields |\n| :--- | :--- | :--- |\n| Domestic | Baidu, Sogou, WeChat | Query, Search Results, Regional Filters |\n| International | Google, Bing, Brave | Snippets, URLs, Time-based Metadata |\n| Specialized | WolframAlpha | Computational Results, Units, Conversions |
Multi Search Engine Advanced Features
- Multi-region support with 8 Chinese and 9 International engines for global coverage.\n- Support for DuckDuckGo Bangs to quickly jump to platforms like GitHub, Stack Overflow, or YouTube.\n- Advanced search operators including exact match, term exclusion, and site-specific indexing.\n- Privacy-first browsing options through integrated engines like Qwant and Startpage.\n- Direct computational knowledge retrieval for math, stocks, and weather via WolframAlpha.
SKILL.md
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