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benjaminjackson
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exa-search

Retrieve relevant web content via semantic search with schema-driven extraction.

3|1|Updated Nov 28, 2025
Search Tags:#summarization#research#semantic search#web search#AI search#data filtering#information discovery
One-click install
npx skills add https://github.com/benjaminjackson/exa-skills --skill exa-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: exa-search
Source: https://github.com/benjaminjackson/exa-skills/tree/main/exa-core/skills/search
Command: npx skills add https://github.com/benjaminjackson/exa-skills --skill exa-search

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires exa-ai, and includes references (resource) components.

What problem does it solve?

This Skill overcomes the limitations of traditional keyword-based search by understanding the meaning behind your queries. It helps you quickly find highly relevant web pages, research papers, news articles, or code repositories, reducing the time spent sifting through irrelevant results.

Core Features & Use Cases

  • Semantic Search: Find content by meaning, not just keywords, for more accurate results.
  • AI-Powered Summarization: Get concise summaries of search results, allowing for quick assessment of relevance.
  • Structured Data Extraction: Define schemas to extract specific information (e.g., titles, key findings) directly from search results.
  • Use Case: Imagine you need to find recent research papers on a specific AI safety topic. Use this Skill to semantically search, filter by category, and extract key findings into a structured format, saving you hours of reading.

Quick Start

Use the exa-search skill to find 5 recent news articles about 'Anthropic Claude new features' and display them concisely.

Frequently Asked Questions about exa-search

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

FAQPage Schema
How does semantic search differ from keyword-based web search?▼

Semantic search understands meaning behind queries rather than matching keywords, retrieving more relevant web pages, research papers, and code repositories by grasping intent and context instead of exact terms.

Can I extract structured data from web search results?▼

Yes, you can define schemas to extract specific information like titles and key findings directly from search results, enabling token-efficient output for RAG pipelines and downstream analysis.

How do I filter web search results by date, category, and result type?▼

Configure controls like --num-results, --type, and --category parameters, plus date filters, to narrow results for rapid discovery, domain-focused filtering, and structured data extraction from web content.

What's the best way to get summaries of search results instead of reading full pages?▼

AI-powered summarization generates concise summaries of search results, allowing quick assessment of relevance and reducing time spent sifting through irrelevant web pages and research papers.

Does semantic search work with research papers, news articles, and code repositories?▼

Yes, semantic search applies to web pages, research papers, news articles, code repositories, and social content, supporting scenarios from rapid discovery to in-depth background research and domain-focused filtering.

Why use semantic search over traditional keyword matching for information discovery?▼

Semantic search overcomes keyword limitations by understanding query meaning, reducing irrelevant results and saving hours when discovering recent content on specific topics like AI safety or emerging technologies.

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