Tavily is an AI-optimized search engine designed to help developers and agents synthesize information and conduct deep web research.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tavily-integration
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 tavily-integration 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 Tavily?
Tavily for Openclaw Skills provides a powerful interface for AI agents to conduct real-time web research, data analysis, and information synthesis. Unlike traditional search engines, Tavily is purpose-built for LLMs and autonomous agents, delivering high-quality, structured results that are easy to parse and integrate into automated workflows.
By leveraging the Membrane infrastructure, this skill removes the complexity of authentication and credential management. It allows developers to focus on building sophisticated research logic while the system handles the underlying API plumbing, ensuring secure and reliable access to Tavily's comprehensive web data.
Tavily Use Cases
- Automated market research and competitive analysis for AI agents.
- Real-time fact-checking and information retrieval during coding or writing tasks.
- Synthesizing long-form articles from web search results into structured data.
- Building autonomous research assistants that require up-to-date web context.
- Automating data collection for SEO and digital marketing reports.
How Tavily Works
- The user authenticates via the Membrane CLI to establish a secure environment for the agent.
- A connection is established to the Tavily API using the connection ensure command, which handles OAuth or API key injection server-side.
- The agent searches for specific research actions (like search or get_article) using natural language intent discovery.
- Actions are executed with JSON parameters to retrieve targeted search results or full article content.
- For custom needs, the agent can send direct proxy requests to any Tavily endpoint with automatic header management.
Tavily Setup
To get started with Tavily and Openclaw Skills, install the Membrane CLI and authenticate your environment:
npm install -g @membranehq/cli@latest
membrane login --tenant --clientName=openclaw
Ensure a valid connection to the Tavily service:
membrane connection ensure "https://tavily.com/" --json
Tavily Data Schema & Taxonomy
The skill organizes data around search results and article content. The following table describes the primary data structures returned:
| Object | Description |
|---|---|
| Search Result | Contains snippets, URLs, and relevance scores for web queries. |
| Article | Full-text content extracted from a specific URL, optimized for LLM consumption. |
| Connection | Metadata regarding the authentication state and service provider configuration. |
| Action Schema | JSON definitions of input parameters and expected output formats for each research tool. |
Tavily Advanced Features
- Natural language action discovery to find the best research tools for a specific query.
- Automated credential refreshing to maintain long-running research tasks without manual intervention.
- Transparent proxy requests for accessing the full breadth of the Tavily API beyond pre-defined actions.
- Support for headless environment authentication using authorization URLs and code completion.
- Machine-readable JSON output for all CLI commands, enabling seamless integration into multi-agent pipelines.
SKILL.md
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