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)
Supported Models:
- gemini-2.5-flash-lite (default) - Fast and cost-effective
- gemini-3-flash-preview - Latest flash model
- gemini-3-pro-preview - More capable, slower
- gemini-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: ```python 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:
1. Missing API Key: Ensure GEMINI_API_KEY is set in the execution environment.
2. Library Missing: Verify that the google-genai library is installed (pip install google-generativeai).
3. API Limits: Check the API usage limits on the Google AI Studio dashboard.
4. Invalid Model: If you set GEMINI_MODEL, ensure it's a valid Gemini model name.
5. Model Not Supporting Grounding: Some models may not support the google_search tool. Use flash or pro variants.