A sophisticated web research skill for AI agents that automates search query deconstruction, web scraping, and structured report synthesis.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install groundapi-web-researcher
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install groundapi-web-researcher using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
GroundAPI Web Researcher is a high-performance tool designed for Openclaw Skills users who require deep, real-time intelligence gathering. By leveraging the GroundAPI MCP server, this skill enables AI agents to move beyond simple search results, allowing them to deconstruct complex topics into multiple search vectors, verify trending topics, and extract full-text content from authoritative sources. It is built to turn raw web data into professional, synthesized research reports with clear citations and actionable insights.
This skill is particularly effective for developers and researchers who need to automate the manual process of information gathering. It handles the nuances of web interaction, such as prioritizing official sources over blogs and managing scraping failures by falling back to search snippets, ensuring that Openclaw Skills users always receive the most reliable data available.
To use this skill within the Openclaw Skills ecosystem, you must have a valid GroundAPI key. Configure your MCP server environment as follows:
{
"mcpServers": {
"groundapi": {
"url": "https://mcp.groundapi.net/mcp",
"headers": {
"X-API-Key": "YOUR_GROUNDAPI_KEY"
}
}
}
}
The GroundAPI Web Researcher organizes data into a structured hierarchy to ensure clarity and traceability:
| Component | Description |
|---|---|
| Overview | A punchy 2-3 sentence summary of the core research conclusions. |
| Key Findings | Bulleted data points grouped by perspective (e.g., Technical, Market, Industry). |
| Insights | A synthesis section distinguishing between objective facts and subjective predictions. |
| Comparison Table | A dimension-based matrix used specifically during 'Comparison Mode'. |
| Source List | A numbered list of all utilized URLs with titles and brief descriptions. |
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