exa-search
Performs AI-powered semantic search and content extraction across the web.
Install
mkdir -p .claude/skills/exa-search-akghosh111 && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15763" && unzip -o skill.zip -d .claude/skills/exa-search-akghosh111 && rm skill.zipInstalls to .claude/skills/exa-search-akghosh111
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Semantic search skill using Exa API for embeddings-based search, similar content discovery, and structured research. Use when you need semantic search, find similar pages, or category-specific searches. Triggers: exa, semantic search, find similar, research paper, github search, 语义搜索, 相似内容Key capabilities
- →Perform semantic search using embeddings to find web pages and research topics
- →Extract full content from search results given result IDs
- →Find similar web pages based on a provided URL
- →Get direct answers to questions using the Exa API
- →Generate structured research output following a given output schema
- →Filter search results by category, domains, published dates, and text content
How it works
This skill uses the Exa API to perform various search operations, including semantic search, content extraction, and finding similar pages. It selects the appropriate Exa endpoint based on the user's intent and constructs a JSON payload for the request.
Inputs & outputs
When to use exa-search
- →Finding similar web pages
- →Performing semantic research
- →Extracting content from search results
About this skill
Exa Search Skill
Trigger Conditions & Endpoint Selection
Choose Exa endpoint based on user intent:
- search: Need semantic search / find web pages / research topics
- contents: Given result IDs, need to extract full content
- findsimilar: Given URL, need to find similar pages
- answer: Need direct answer to a question
- research: Need structured research output following given
output_schema
Recommended Architecture (Main Skill + Sub-skill)
This skill uses a two-phase architecture:
- Main skill (current context): Understand user question → Choose endpoint → Assemble JSON payload
- Sub-skill (fork context): Only responsible for HTTP call execution, avoiding conversation history token waste
Execution Method
Use Task tool to invoke exa-fetcher sub-skill, passing command and JSON (stdin):
Task parameters:
- subagent_type: Bash
- description: "Call Exa API"
- prompt: cat <<'JSON' | node .claude/skills/exa-search/exa-api.cjs <search|contents|findsimilar|answer|research>
{ ...payload... }
JSON
Payload Examples
1) Search
cat <<'JSON' | node .claude/skills/exa-search/exa-api.cjs search
{
"query": "Latest research in LLMs",
"type": "auto",
"numResults": 10,
"category": "research paper",
"includeDomains": [],
"excludeDomains": [],
"startPublishedDate": "2025-01-01",
"endPublishedDate": "2025-12-31",
"includeText": [],
"excludeText": [],
"context": true,
"contents": {
"text": true,
"highlights": true,
"summary": true
}
}
JSON
Search Types:
neural: Semantic search using embeddingsfast: Quick keyword-based searchauto: Automatically choose best method (default)deep: Comprehensive deep search
Categories:
company,people,research paper,news,pdf,github,tweet, etc.
2) Contents
cat <<'JSON' | node .claude/skills/exa-search/exa-api.cjs contents
{
"ids": ["result-id-1", "result-id-2"],
"text": true,
"highlights": true,
"summary": true
}
JSON
3) Find Similar
cat <<'JSON' | node .claude/skills/exa-search/exa-api.cjs findsimilar
{
"url": "https://example.com/article",
"numResults": 10,
"category": "news",
"includeDomains": [],
"excludeDomains": [],
"startPublishedDate": "2025-01-01",
"contents": {
"text": true,
"summary": true
}
}
JSON
4) Answer
cat <<'JSON' | node .claude/skills/exa-search/exa-api.cjs answer
{
"query": "What is the capital of France?",
"numResults": 5,
"includeDomains": [],
"excludeDomains": []
}
JSON
5) Research
cat <<'JSON' | node .claude/skills/exa-search/exa-api.cjs research
{
"input": "What are the latest developments in AI?",
"model": "auto",
"stream": false,
"output_schema": {
"properties": {
"topic": {
"type": "string",
"description": "The main topic"
},
"key_findings": {
"type": "array",
"description": "List of key findings",
"items": {
"type": "string"
}
}
},
"required": ["topic"]
},
"citation_format": "numbered"
}
JSON
Environment Variables & API Key
Two ways to configure API Key (priority: environment variable > .env):
- Environment variable:
EXA_API_KEY .envfile: Place in.claude/skills/exa-search/.env, can copy from.env.example
Response Format
All endpoints return JSON with:
requestId: Unique request identifierresults: Array of search resultssearchType: Type of search performed (for search endpoint)context: LLM-friendly context string (if requested)costDollars: Detailed cost breakdown
When not to use it
- →The task requires searching outside the web content indexed by Exa
- →The task requires real-time data not yet indexed by Exa
- →The task requires accessing private or restricted content not publicly available
Prerequisites
Limitations
- →The skill relies on the Exa API for all search and content retrieval operations
- →The search capabilities are limited to the types and categories supported by Exa
- →The output schema for research must be defined in the input
How it compares
This skill use the Exa API's embeddings-based search and content extraction capabilities, providing semantic understanding and structured output that goes beyond keyword-based search engines.
Compared to similar skills
exa-search side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| exa-search (this skill) | 0 | 6mo | Review | Intermediate |
| exa-search | 9 | 8mo | Review | Beginner |
| tavily-usage | 5 | 8mo | No flags | Beginner |
| startup-validator | 1 | 9mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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