exa-search
Semantic search, similar content discovery, and structured research using Exa API. Use when you need semantic/embeddings-based search, finding similar content, or searching by category (company, people, research papers, etc.).
exa-search
Overview
Semantic search, similar content discovery, and structured research using Exa API
When to Use
- When you need semantic/embeddings-based search
- When finding similar content
- When searching by category (company, people, research papers, etc.)
Installation
npx skills add -g BenedictKing/exa-searchStep-by-Step Guide
- Install the skill using the command above
- Configure Exa API key
- Use naturally in Claude Code conversations
Examples
See GitHub Repository for examples.
Best Practices
- Configure API keys via environment variables
Troubleshooting
See the GitHub repository for troubleshooting guides.
Related Skills
- context7-auto-research, tavily-web, firecrawl-scraper, codex-review
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Details
| Source | community |
|---|---|
| License | — |
| Risk label | critical ("critical" means the skill may run commands or touch files — read before use) |
| Files | SKILL.md |
| Added | 2026-02-27 |
Related skills
ai-engineering-toolkit
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
clarity-gate
Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.
embedding-strategies
Guide to selecting and optimizing embedding models for vector search applications.
llm-app-patterns
Architecture and integration sketches for LLM applications, with explicit retrieval, tool, privacy and verification boundaries.
local-llm-expert
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
notebooklm
Interact with Google NotebookLM to query documentation with Gemini's source-grounded answers. Each question opens a fresh browser session, retrieves the answer exclusively from your uploaded documents, and closes.