A high-performance, multi-engine web search aggregator that provides comprehensive search results without requiring any API keys.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-engine-websearch
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-engine-websearch 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 WebSearch Multi-Engine Aggregator?
WebSearch is a local search skill designed for AI agents to query six major search engines simultaneously: DuckDuckGo, DDG Lite, Yahoo, Yahoo JP, Startpage, and Google. By leveraging parallel execution and headless browser technology, this Openclaw Skills contribution delivers high-quality search data while maintaining privacy and avoiding the costs of paid search APIs. It automatically merges, deduplicates, and ranks results based on their frequency across different engines, ensuring the most relevant information is prioritized for the user.
This skill is built for speed and resilience, utilizing Python's ThreadPoolExecutor to run queries in parallel. While engines like DuckDuckGo are scraped via lightweight HTTP requests, Google results are fetched using a headless Chromium instance to ensure modern web compatibility. This makes it an essential tool for developers building agents that require fresh, real-time information from the web.
WebSearch Multi-Engine Aggregator Use Cases
- Conducting deep research across multiple information sources simultaneously to ensure data accuracy.
- Verifying facts using real-time web data and cross-engine consensus.
- Finding recent news, technical articles, or product documentation that might be indexed differently across engines.
- Gathering diverse perspectives on specific topics by aggregating results from regional engines like Yahoo JP.
- Performing high-volume searches for data collection without worrying about API limits or subscription costs.
How WebSearch Multi-Engine Aggregator Works
- The skill receives a search query via the command line and triggers parallel requests to the six supported search engines.
- It utilizes lightweight HTTP scraping for engines like DuckDuckGo and Yahoo, while using headless Chromium via Playwright for Google to handle JavaScript-rendered results.
- All retrieved results are aggregated into a single data pool in real-time.
- The system deduplicates URLs and calculates a ranking score based on how many engines returned the same link, known as cross-engine frequency.
- A structured JSON response is generated, containing the ranked results, snippets, and source metadata for the Openclaw Skills agent to process and summarize.
WebSearch Multi-Engine Aggregator Setup
To get started with WebSearch, ensure you have Python 3.9+ installed on your system. You can install the skill using the ClawHub CLI:
npx clawhub@latest install multi-engine-websearch
After installation, you must set up the Playwright browser dependencies required for Google search functionality:
pip3 install playwright
python3 -m playwright install chromium
You can then run a search directly from the terminal:
python3 ~/.openclaw/workspace/skills/websearch/scripts/search.py "your query" --json
WebSearch Multi-Engine Aggregator Data Schema & Taxonomy
The skill produces a structured JSON output designed for programmatic consumption. It includes metadata about the search process and an array of ranked results.
| Field | Type | Description |
|---|---|---|
query |
String | The original search term used. |
total |
Integer | Total number of unique results found across all engines. |
engines |
Object | A breakdown of result counts provided by each individual engine. |
results |
Array | A list of result objects containing title, url, snippet, and an array of source engines. |
Results appearing in multiple engines are automatically moved to the top of the list to reflect higher relevance and consensus.
WebSearch Multi-Engine Aggregator Advanced Features
- Parallel execution using ThreadPoolExecutor for rapid result retrieval across six different sources.
- Cross-engine consensus ranking which identifies the most authoritative results based on multi-platform appearance.
- Resilient architecture where individual engine failures are handled gracefully without disrupting the overall search operation.
- Support for custom engine selection via the
--enginesflag, allowing users to filter specific sources. - Headless browser integration for Google, enabling the retrieval of results from JS-heavy search pages while maintaining a local footprint.
- Built-in deduplication to ensure the AI agent receives a clean list of unique URLs for processing within the Openclaw Skills ecosystem.
SKILL.md
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