Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/tomevault-io/skills-registry --skill exa명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
| Use when this capability is needed.
> Use when this capability is needed.
Review architecture and API design for the vfs-s3 project. Use when the user mentions @architect, asks to review an issue's design, discuss module boundaries, API shape, or architectural decisions for vfs-s3. Also trigger when the user wants to create an ADR (Architecture Decision Record) or evaluate a technical approach for the project. Intended for dispatch from Codex automation or Claude routines; GitHub trigger phrase: @vfs-s3-bot please prepare design doc Use when this capability is needed.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | exa |
| description | | Use when this capability is needed. |
High-precision semantic search via Exa API. Standalone CLI only (no MCP dependency).
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)
# 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]
# 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]
# 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
# Check config and test connection
python scripts/exa_cli.py get_config_info [--no-test]
| Tool | Required | Optional | Output |
|---|---|---|---|
web_search_exa | query | num-results, type, livecrawl | Search results JSON |
web_search_advanced_exa | query | include-domains, exclude-domains, start-date, end-date, text, highlights, summary | Filtered results JSON |
deep_search_exa | objective | additional-queries | Expanded search results |
company_research_exa | company | num-results | Company info JSON |
linkedin_search_exa | query | num-results | LinkedIn profiles JSON |
crawling_exa | url | max-chars, livecrawl, text, highlights, summary | Page content JSON |
get_code_context_exa | query | tokens-num (1000-50000) | Code context JSON |
deep_researcher_start | instructions | model | Task ID |
deep_researcher_check | task-id | - | Status + report |
| Use Case | Recommended Tool |
|---|---|
| Real-time news, current events | grok-search |
| Semantic/conceptual research | exa |
| Code documentation lookup | exa (get_code_context_exa) |
| Company/professional research | exa |
| General web content fetch | grok-search |
| Academic papers, technical docs | exa |
| AI-powered deep research | exa (deep_researcher_*) |
python scripts/exa_cli.py web_search_exa --query "best practices for React hooks" --num-results 5
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
# 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 | Recovery |
|---|---|
EXA_API_KEY not configured | Set environment variable or use --api-key |
| HTTP 429 (Rate limit) | Automatic retry with exponential backoff |
| HTTP 401 (Unauthorized) | Verify API key is valid |
| Timeout | Retry or reduce num-results |
All commands output JSON to stdout. Use --out <file> to write to file instead.
{
"results": [
{"title": "...", "url": "...", "text": "...", "publishedDate": "..."}
]
}
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