Google Web Search
Enables grounded question answering by automatically executing the Google Search tool within Gemini models. Use when the required information is recent (post knowledge cutoff) or requires verifiable c
Enables grounded question answering by automatically executing the Google Search tool within Gemini models. Use when the required information is recent (post knowledge cutoff) or requires verifiable c
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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:
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.
The core logic is in
scripts/example.py. This script requires the following environment variables:
gemini-2.5-flash-lite)Supported Models:
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 versionWhen 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_responseBasic 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)
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.No automatic installation available. Please visit the source repository for installation instructions.
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