Perform Semantic Search and Content Discovery
Use Exa API for semantic search, similar-content discovery, and category-focused research in Claude Code conversations.
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Why it matters
Leverage semantic search and content discovery capabilities to find similar information and conduct structured research. This skill is ideal for tasks requiring embeddings-based search across various categories.
Outcomes
What it gets done
Perform semantic search using Exa API.
Discover similar content based on embeddings.
Conduct structured research by category (e.g., companies, research papers).
Extract relevant information for further analysis.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-exa-search | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
Reports
Agent outcome reports
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Overview
Exa Search is a community skill for semantic search, similar-content discovery, and structured research using Exa API. It supports category-focused searches for companies, people, and research papers. Use it when semantic relevance or finding related content is the task's main requirement. Install the skill and configure the Exa API key before conversational use.
What it does
Exa Search brings semantic search, similar-content discovery, and structured research using Exa API into a conversational skill. Its scope includes embeddings-based search and category-focused research, with companies, people, and research papers named as example categories.
The supported use cases are finding content by semantic relevance, locating similar material, and narrowing research to a category. These are the reasons to choose the skill when a search task matches its described scope.
When to use - and when NOT to
Use this skill when semantic search or related-content discovery is central to the request. Category-based searches are another stated fit. Keep use within those boundaries and clarify missing inputs, permissions, safety boundaries, or success criteria before proceeding.
Apply environment-specific validation, testing, or expert review where the task calls for it. Search output should therefore be reviewed in the context of the research rather than treated as a replacement for those checks.
Inputs and outputs
Setup requires the installed skill and an Exa API key. Requests are then made naturally in Claude Code conversations. The workflow produces semantic search or similar-content research results according to the requested category and search purpose.
Install the skill with this command:
npx skills add -g BenedictKing/exa-search
Configure API keys through environment variables. The referenced GitHub repository is the destination for additional examples and troubleshooting guidance.
Integrations
Exa API supplies the search capability, and Claude Code is the stated conversational environment. Related skills include context7-auto-research, tavily-web, firecrawl-scraper, and codex-review.
FAQ
Common questions
Discussion
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