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High-precision semantic search and content retrieval via Exa API. Use when: (1) Deep research requiring semantic understanding, (2) Code documentation and examples lookup, (3) Company/professional research, (4) AI-powered comprehensive research tasks, (5) URL content extraction with structured output. Triggers: "research", "find papers", "code examples", "company info", "LinkedIn profiles", "deep analysis". Differentiator: Exa excels at semantic/neural search while grok-search is better for real-time news and general web content.

57 stars
1.2k downloads
Updated 2/11/2026

Package Files

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SKILL.md

Exa Search

High-precision semantic search via Exa API. Standalone CLI only (no MCP dependency).

Execution Method

Run scripts/exa_cli.py via Bash:

# Prerequisites: pip install httpx tenacity
# Environment: EXA_API_KEY (required), EXA_API_URL (optional, default: https://api.exa.ai)

Available Tools

Search Tools

# Basic semantic search
python scripts/exa_cli.py web_search_exa --query "emerging patterns in TypeScript" [--num-results 10] [--type auto|keyword|neural] [--livecrawl always|fallback|never]

# Advanced search with filters
python scripts/exa_cli.py web_search_advanced_exa --query "machine learning papers" \
  [--include-domains arxiv.org,github.com] [--exclude-domains medium.com] \
  [--start-date 2024-01-01] [--end-date 2024-12-31] \
  [--text] [--highlights] [--summary] [--out results.json]

# Deep search with query expansion
python scripts/exa_cli.py deep_search_exa --objective "foundations of quantum error correction" [--additional-queries "query1|query2"]

# Company research
python scripts/exa_cli.py company_research_exa --company "Anthropic" [--num-results 10]

# LinkedIn profile search
python scripts/exa_cli.py linkedin_search_exa --query "AI researchers at Stanford" [--num-results 10]

Content Tools

# Extract content from URL
python scripts/exa_cli.py crawling_exa --url "https://example.com/article" \
  [--max-chars 5000] [--livecrawl always|fallback|never] \
  [--text] [--highlights] [--summary] [--out content.json]

# Get code context (documentation, examples)
python scripts/exa_cli.py get_code_context_exa --query "React useState hook examples" [--tokens-num 10000] [--out code.json]

Research Tools

# Start AI research task
python scripts/exa_cli.py deep_researcher_start --instructions "Analyze the impact of LLMs on software development" [--model exa-research|exa-research-pro]
# Returns: {"taskId": "abc123", ...}

# Check research status
python scripts/exa_cli.py deep_researcher_check --task-id "abc123" [--out report.json]
# Status: running → completed | failed

Configuration

# Check config and test connection
python scripts/exa_cli.py get_config_info [--no-test]

Tool Capability Matrix

ToolRequiredOptionalOutput
web_search_exaquerynum-results, type, livecrawlSearch results JSON
web_search_advanced_exaqueryinclude-domains, exclude-domains, start-date, end-date, text, highlights, summaryFiltered results JSON
deep_search_exaobjectiveadditional-queriesExpanded search results
company_research_exacompanynum-resultsCompany info JSON
linkedin_search_exaquerynum-resultsLinkedIn profiles JSON
crawling_exaurlmax-chars, livecrawl, text, highlights, summaryPage content JSON
get_code_context_exaquerytokens-num (1000-50000)Code context JSON
deep_researcher_startinstructionsmodelTask ID
deep_researcher_checktask-id-Status + report

Tool Routing Guide

Exa vs Grok-Search

Use CaseRecommended Tool
Real-time news, current eventsgrok-search
Semantic/conceptual researchexa
Code documentation lookupexa (get_code_context_exa)
Company/professional researchexa
General web content fetchgrok-search
Academic papers, technical docsexa
AI-powered deep researchexa (deep_researcher_*)

Workflow Patterns

Pattern 1: Quick Semantic Search

python scripts/exa_cli.py web_search_exa --query "best practices for React hooks" --num-results 5

Pattern 2: Filtered Research

python scripts/exa_cli.py web_search_advanced_exa --query "transformer architecture" \
  --include-domains arxiv.org,papers.nips.cc --start-date 2023-01-01 --text --summary

Pattern 3: Deep Research Task

# Start research
python scripts/exa_cli.py deep_researcher_start --instructions "Compare RAG vs fine-tuning for domain adaptation"
# Poll until completed
python scripts/exa_cli.py deep_researcher_check --task-id "<taskId>" --out research_report.json

Error Handling

ErrorRecovery
EXA_API_KEY not configuredSet environment variable or use --api-key
HTTP 429 (Rate limit)Automatic retry with exponential backoff
HTTP 401 (Unauthorized)Verify API key is valid
TimeoutRetry or reduce num-results

Output Format

All commands output JSON to stdout. Use --out <file> to write to file instead.

{
  "results": [
    {"title": "...", "url": "...", "text": "...", "publishedDate": "..."}
  ]
}

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

88/100Analyzed 2/24/2026

High-quality technical reference skill for Exa semantic search API. Comprehensive documentation with 9 tools, clear command examples, capability matrix, routing guide comparing Exa vs Grok-Search, workflow patterns, and error handling. Well-structured with triggers and use cases. Located in dedicated skills folder, uses public API - highly reusable."

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Metadata

Licenseunknown
Version-
Updated2/11/2026
PublisherDianel555

Tags

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