What makes Exa search different from standard keyword search?

Exa uses semantic embeddings to find results based on meaning and context rather than just keyword matching, providing much more relevant data for complex technical queries.

How does this skill optimize token usage in Claude Code?

It provides a 'toon' format for 40% token reduction and supports JSON schemas with jq to extract only the specific fields needed, which can reduce token usage by up to 90%.

How does the cost optimization strategy work?

The skill encourages staying within the 1-25 result bracket to minimize costs and suggests running multiple targeted searches instead of high-volume queries to maintain quality and efficiency.

Can I extract specific data from web pages automatically?

Yes, by using the --summary-schema flag, you can define a custom JSON schema to have the AI extract specific structured fields from the search results.

Can I use this for LinkedIn research or company profiles?

Yes, the exa-search skill includes dedicated LinkedIn flags to search specifically for company pages or individual professional profiles.

Exa Semantic Web Search

Name: Exa Semantic Web Search
Author: benjaminjackson

bybenjaminjackson

•

Web Scraping & Data Collection

Empowers Claude with AI-powered semantic search to find web content, research papers, and code repositories by meaning rather than keywords.

About

Exa Semantic Web Search integrates Exa.ai's advanced search capabilities directly into Claude Code, allowing developers to perform deep, meaning-based research. Unlike traditional keyword search, this skill understands the context of queries to return highly relevant results, including news articles, documentation, and LinkedIn profiles. It features built-in token optimization strategies, such as toon formatting and JSON schema extraction, ensuring that your web-assisted coding tasks remain cost-effective and efficient by reducing token consumption by up to 90% through precise data filtering.

Key Features

Structured data extraction using custom JSON schemas and jq integration.
Cost-optimized search tiers with smart result limiting and multi-query strategies.
2 GitHub stars
Token-efficient output formats like 'toon' to save up to 40% on token usage.
Semantic AI search for finding content by meaning rather than keywords.
Specialized search filters for LinkedIn, research papers, and news articles.

Use Cases

Finding specific code repositories or technical implementations relevant to project goals.
Researching the latest AI architecture papers or library documentation during development.
Extracting structured summaries of news or company profiles for data-driven tasks.

About

Key Features

Structured data extraction using custom JSON schemas and jq integration.
Cost-optimized search tiers with smart result limiting and multi-query strategies.
2 GitHub stars
Token-efficient output formats like 'toon' to save up to 40% on token usage.
Semantic AI search for finding content by meaning rather than keywords.
Specialized search filters for LinkedIn, research papers, and news articles.

Use Cases

Finding specific code repositories or technical implementations relevant to project goals.
Researching the latest AI architecture papers or library documentation during development.
Extracting structured summaries of news or company profiles for data-driven tasks.