web-search

Search the web and retrieve news via Tavily with optional filters.

6|2|Updated Nov 16, 2025
One-click install
npx skills add https://github.com/EricOo0/stock-trading-platform --skill web-search-ericoo0
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: web-search
Source: https://github.com/EricOo0/stock-trading-platform/tree/main/backend/skills/web-search
Command: npx skills add https://github.com/EricOo0/stock-trading-platform --skill web-search-ericoo0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires tavily-python, and includes scripts (resource) components.

What problem does it solve?

This skill solves the problem of quickly finding relevant information on the web and tracking news via Tavily, enabling timely insights without manual search effort.

Core Features & Use Cases

  • Web search via Tavily for general information retrieval and trend monitoring.
  • News tracking with optional topic, days, and domains filters for focused monitoring and source gathering.
  • Use Case: A market researcher needs up-to-date AI news and supporting sources for a brief.

Quick Start

Run a simple search example to fetch latest results: python scripts/search.py "AI trends" --topic general --days 7

Frequently Asked Questions about web-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I get web search results in JSON format using Python?

Web search results in JSON format are retrieved by running a Python script that queries the Tavily API. The script outputs a structured JSON list containing fields like title, href, body, and score for each result.

Can I filter news tracking results by specific domains and timeframes?

News tracking results can be filtered using optional topic, days, and domain parameters. This enables focused monitoring and source gathering for specific timeframes and websites via the Tavily API.

Do I need a Tavily API key to perform web searches in a Python environment?

A Tavily API key is required to perform web searches. The script operates within a Python environment and uses the tavily-python dependency to authenticate requests and retrieve information.

What is the best way to track AI trends and gather supporting sources for a brief?

The best way to track AI trends is using news retrieval with topic and days filters. Running a search query via Tavily provides up-to-date results and supporting sources structured as a JSON list for analysis.

Does this web search approach return relevance scores for retrieved information?

The web search approach returns a structured JSON list that includes a score field for each result. This score indicates the relevance of the retrieved information to the original search query.

How do I run a quick search example to fetch the latest web results?

To fetch the latest web results, run the Python script with arguments specifying the query, topic, and days. For example: python scripts/search.py "AI trends" --topic general --days 7.