A dynamic tool discovery and execution layer that connects AI agents to thousands of external APIs via a single unified interface.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install qverisai
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 qverisai 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 qverisai?
qverisai is a powerful integration for Openclaw Skills that enables AI agents to search for and invoke specialized tools on the fly. Instead of hardcoding every individual API, this skill uses the QVeris API to locate relevant capabilities—ranging from real-time weather data to complex financial analysis—and execute them with specific parameters. It acts as a bridge to a vast ecosystem of third-party services, providing a simplified workflow for tool invocation.
This approach significantly expands the reach of Openclaw Skills, allowing agents to handle diverse tasks like clinical trial searches, image generation, and social media analytics without needing a custom integration for each provider. By abstracting the complexity of multiple API formats into a searchable interface, it empowers developers to build more versatile and responsive AI agents.
qverisai Use Cases
- Retrieval of real-time weather, stock prices, and economic indicators.
- Searching for latest tech news, trending social media topics, or news headlines.
- Accessing health data including clinical trials and drug information.
- Generating AI content such as images or text-to-speech through AIGC tools.
- Performing geolocation tasks like IP lookups and reverse geocoding.
How qverisai Works
- The agent searches for a capability by description (e.g., "weather forecast API") rather than specific parameters.
- The QVeris API returns a list of matching tools, including metadata like success rates and average execution times.
- The user or agent selects the most appropriate tool based on the ranked search results.
- The chosen tool is executed using a unique search_id, the specific tool_id, and the required parameters in JSON format.
qverisai Setup
Obtain your API key from the QVeris dashboard. Ensure your environment has Node.js installed, then configure the environment variable:
export QVERIS_API_KEY='your_api_key_here'
To search for a tool using the CLI:
node scripts/qveris_tool.mjs search "weather forecast API"
To execute a discovered tool:
node scripts/qveris_tool.mjs execute openweathermap_current_weather --search-id <id> --params '{"city": "London", "units": "metric"}'
qverisai Data Schema & Taxonomy
The qverisai skill manages data through structured API responses and specific CLI flags to ensure reliability within Openclaw Skills.
| Feature | Description |
|---|---|
| Input Parameters | Managed via the --params flag as a JSON string |
| Tracking | Uses a search_id to link execution to a previous discovery phase |
| Tool Metadata | Includes success_rate, avg_execution_time, and capability descriptions |
| Credentials | Secured via the QVERIS_API_KEY environment variable |
qverisai Advanced Features
- Automated tool selection based on historical performance metrics like success rates and latency.
- Support for scoped, revocable API keys to maintain high security standards within Openclaw Skills implementations.
- Flexible response handling with adjustable timeouts and maximum data size limits to prevent agent memory overflow.
- CLI-based raw JSON output mode for seamless integration into larger automation pipelines and multi-agent workflows.
SKILL.md
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