google-web-search
Enables grounded question answering by automatically executing the Google Search tool within Gemini models.
Installation
npx clawhub@latest install google-web-searchView the full skill documentation and source below.
Documentation
Google Web Search
Overview
This skill provides the capability to perform real-time web searches via the Gemini API's google_search grounding tool. It is designed to fetch the most current information available on the web to provide grounded, citable answers to user queries.
Key Features:
- Real-time web search via Gemini API
- Grounded responses with verifiable citations
- Configurable model selection
- Simple Python API
Usage
This skill exposes the Gemini API's google_search tool. It should be used when the user asks for real-time information, recent events, or requests verifiable citations.
Execution Context
The core logic is in scripts/example.py. This script requires the following environment variables:
- GEMINI_API_KEY (required): Your Gemini API key
- GEMINI_MODEL (optional): Model to use (default:
gemini-2.5-flash-lite)
gemini-2.5-flash-lite(default) - Fast and cost-effectivegemini-3-flash-preview- Latest flash modelgemini-3-pro-preview- More capable, slowergemini-2.5-flash-lite-preview-09-2025- Specific version
Python Tool Implementation Pattern
When integrating this skill into a larger workflow, the helper script should be executed in an environment where the google-genai library is available and the GEMINI_API_KEY is exposed.
Example Python invocation structure:
from skills.google-web-search.scripts.example import get_grounded_response
# Basic usage (uses default model):
prompt = "What is the latest market trend?"
response_text = get_grounded_response(prompt)
print(response_text)
# Using a specific model:
response_text = get_grounded_response(prompt, model="gemini-3-pro-preview")
print(response_text)
# Or set via environment variable:
import os
os.environ["GEMINI_MODEL"] = "gemini-3-flash-preview"
response_text = get_grounded_response(prompt)
print(response_text)
Troubleshooting
If the script fails:
GEMINI_API_KEY is set in the execution environment.google-genai library is installed (pip install google-generativeai).GEMINI_MODEL, ensure it's a valid Gemini model name.google_search tool. Use flash or pro variants.