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everything-claude-code/.agents/skills/exa-search/SKILL.md
2026-03-12 15:07:57 -07:00

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---
name: exa-search
description: Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
origin: ECC
---
# Exa Search
Neural search for web content, code, companies, and people via the Exa MCP server.
## When to Activate
- User needs current web information or news
- Searching for code examples, API docs, or technical references
- Researching companies, competitors, or market players
- Finding professional profiles or people in a domain
- Running background research for any development task
- User says "search for", "look up", "find", or "what's the latest on"
## MCP Requirement
Exa MCP server must be configured. Add to `~/.claude.json`:
```json
"exa-web-search": {
"command": "npx",
"args": [
"-y",
"exa-mcp-server",
"tools=web_search_exa,web_search_advanced_exa,get_code_context_exa,crawling_exa,company_research_exa,linkedin_search_exa,deep_researcher_start,deep_researcher_check"
],
"env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
}
```
Get an API key at [exa.ai](https://exa.ai).
## Core Tools
### web_search_exa
General web search for current information, news, or facts.
```
web_search_exa(query: "latest AI developments 2026", numResults: 5)
```
**Parameters:**
| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `query` | string | required | Search query |
| `numResults` | number | 8 | Number of results |
### web_search_advanced_exa
Filtered search with domain and date constraints.
```
web_search_advanced_exa(
query: "React Server Components best practices",
numResults: 5,
includeDomains: ["github.com", "react.dev"],
startPublishedDate: "2025-01-01"
)
```
**Parameters:**
| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `query` | string | required | Search query |
| `numResults` | number | 8 | Number of results |
| `includeDomains` | string[] | none | Limit to specific domains |
| `excludeDomains` | string[] | none | Exclude specific domains |
| `startPublishedDate` | string | none | ISO date filter (start) |
| `endPublishedDate` | string | none | ISO date filter (end) |
### get_code_context_exa
Find code examples and documentation from GitHub, Stack Overflow, and docs sites.
```
get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)
```
**Parameters:**
| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `query` | string | required | Code or API search query |
| `tokensNum` | number | 5000 | Content tokens (1000-50000) |
### company_research_exa
Research companies for business intelligence and news.
```
company_research_exa(companyName: "Anthropic", numResults: 5)
```
**Parameters:**
| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `companyName` | string | required | Company name |
| `numResults` | number | 5 | Number of results |
### people_search_exa
Find professional profiles and bios.
```
people_search_exa(query: "AI safety researchers at Anthropic", numResults: 5)
```
### crawling_exa
Extract full page content from a URL.
```
crawling_exa(url: "https://example.com/article", tokensNum: 5000)
```
**Parameters:**
| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `url` | string | required | URL to extract |
| `tokensNum` | number | 5000 | Content tokens |
### deep_researcher_start / deep_researcher_check
Start an AI research agent that runs asynchronously.
```
# Start research
deep_researcher_start(query: "comprehensive analysis of AI code editors in 2026")
# Check status (returns results when complete)
deep_researcher_check(researchId: "<id from start>")
```
## Usage Patterns
### Quick Lookup
```
web_search_exa(query: "Node.js 22 new features", numResults: 3)
```
### Code Research
```
get_code_context_exa(query: "Rust error handling patterns Result type", tokensNum: 3000)
```
### Company Due Diligence
```
company_research_exa(companyName: "Vercel", numResults: 5)
web_search_advanced_exa(query: "Vercel funding valuation 2026", numResults: 3)
```
### Technical Deep Dive
```
# Start async research
deep_researcher_start(query: "WebAssembly component model status and adoption")
# ... do other work ...
deep_researcher_check(researchId: "<id>")
```
## Tips
- Use `web_search_exa` for broad queries, `web_search_advanced_exa` for filtered results
- Lower `tokensNum` (1000-2000) for focused code snippets, higher (5000+) for comprehensive context
- Combine `company_research_exa` with `web_search_advanced_exa` for thorough company analysis
- Use `crawling_exa` to get full content from specific URLs found in search results
- `deep_researcher_start` is best for comprehensive topics that benefit from AI synthesis
## Related Skills
- `deep-research` — Full research workflow using firecrawl + exa together
- `market-research` — Business-oriented research with decision frameworks