功能描述

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 citation.

使用说明 (SKILL.md)

Google Web Search

Name: Google Web Search
Author: theoseo

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:

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:

Missing API Key: Ensure GEMINI_API_KEY is set in the execution environment.
Library Missing: Verify that the google-genai library is installed (pip install google-generativeai).
API Limits: Check the API usage limits on the Google AI Studio dashboard.
Invalid Model: If you set GEMINI_MODEL, ensure it's a valid Gemini model name.
Model Not Supporting Grounding: Some models may not support the google_search tool. Use flash or pro variants.

安全使用建议

This skill appears to do what it claims: call Gemini's google_search grounding tool. Before installing, 1) ensure you supply a Gemini API key with minimal permissions (rotate/restrict the key where possible), 2) run the pip install in an isolated Python environment (venv/container) to avoid contaminating system packages, 3) be aware the code will read environment variables and will also load a local .env file if present (remove or audit any .env files that contain unrelated secrets), and 4) review network/policy requirements for allowing outbound calls to Google's API from the environment where you run this skill.

功能分析

Type: OpenClaw Skill Name: google-web-search Version: 1.0.3 The OpenClaw skill 'google-web-search' is classified as benign. Its core functionality involves using the official Google GenAI library to interact with the Gemini API for web search grounding, as stated in its purpose. API keys are securely loaded from environment variables, and dependencies are installed via standard `pip install -r requirements.txt` (or `uv sync`) commands from local files, which is a common and necessary practice for Python skills. There is no evidence of data exfiltration, backdoors, unauthorized remote execution, or prompt injection attempts against the OpenClaw agent itself. All actions are aligned with the skill's stated goal of providing grounded web search capabilities.

能力评估

✓ Purpose & Capability

Name/description match the implementation: the skill uses google-genai to call Gemini's google_search grounding tool. The only required credential is GEMINI_API_KEY and the listed Python dependencies (google-genai, pydantic-settings) are exactly what you'd expect for this functionality.

ℹ Instruction Scope

SKILL.md instructs installing the Python deps and invoking scripts/example.py. The runtime code reads GEMINI_API_KEY (and optionally GEMINI_MODEL) from the environment. The pydantic BaseSettings config references an env_file '.env', so the skill may also load variables from a local .env file in the working directory — this is not malicious but worth noting because it can pull secrets from .env files if present.

✓ Install Mechanism

No custom download or executable installer; install is just 'pip install -r requirements.txt' for standard PyPI packages. The declared dependencies are reasonable and traceable (google-genai, pydantic-settings).

✓ Credentials

Only GEMINI_API_KEY is required (GEMINI_MODEL optional). No unrelated credentials, system config paths, or broad secret requests are present. The use of .env means local environment files can supply the key, which is expected for this kind of skill.

✓ Persistence & Privilege

Skill is not forced-always and does not request elevated platform privileges. It can be invoked autonomously (default), which is normal for skills; there is no evidence it modifies other skills or system-wide settings.

版本历史

v1.0.3

Simplify install to standard pip, add clear documentation for uv and credentials

v1.0.2

Add metadata: required credentials (GEMINI_API_KEY) and install steps for Python dependencies

v1.0.1

- No code or documentation changes detected in this release. - Version bump only; functionality remains unchanged.

v1.0.0

- Initial release of the Google Web Search skill. - Enables real-time, grounded question answering by leveraging the Gemini API's google_search tool. - Provides citable answers for recent events or information beyond the knowledge cutoff. - Supports configurable Gemini models, with simple Python API integration. - Includes troubleshooting tips and example usage in Python.

元数据

Slug google-web-search

版本 1.0.3

许可证 —

累计安装 10

当前安装数 8

历史版本数 4

常见问题