exa

The Exa skill provides direct access to the Exa neural search engine, enabling AI agents to perform semantic web searches and extract precise code context. Unlike traditional keyword-based search engines, Exa is optimized for AI-driven information retrieval, making it a critical tool for developers, data scientists, and researchers who need to navigate vast technical landscapes efficiently. By utilizing neural embeddings, the skill delivers highly relevant search results for documentation, research papers, GitHub repositories, and corporate entities.

• Neural search capabilities: Perform targeted searches using auto, neural, fast, or deep modes to balance speed and accuracy.

• Intelligent code context: Retrieve relevant code snippets and documentation directly from the web to assist in solving complex programming tasks.

• Multi-category support: Filter results across specific domains such as github, research-paper, pdf, company, news, and tweet.

• Content extraction: Extract full text from URLs to streamline reading and analysis within the agent workflow.

• API-driven integration: Requires an EXA_API_KEY to authenticate and leverage the full power of the Exa AI infrastructure.

• Practical usage tips: Use the search.sh script for broad queries and the code.sh script when you specifically need technical implementations or documentation context.

• Inputs/Outputs: The skill accepts natural language search queries and optional parameters like result count and source categories, returning text snippets, URLs, or full content extracts.

• Constraints: Requires the EXA_API_KEY environment variable to be set; network access is required to connect to the Exa AI API.

• Best practices: For technical tasks, use the 'neural' search type to ensure that retrieved content is semantically aligned with your specific code or architectural requirements.