exa-search（前搜索） Skills下载安装命令和教程

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手，先确认命令和权限，再让它执行。

请帮我安装这个 Agent Skill：exa-search（前搜索）
来源仓库：https://github.com/tdimino/claude-code-minoan
仓库路径：skills/exa-search
安装命令：
npx skills add https://github.com/tdimino/claude-code-minoan --skill exa-search
安装前请先检查当前环境是否支持对应 CLI，并向我确认将要执行的命令、安装目录、联网范围和文件读写权限；确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill；本站只展示命令，不托管安装包，也不自动执行。

skills.shnpx skills

npx skills add https://github.com/tdimino/claude-code-minoan --skill exa-search

简介

exa-search 用于查找、检索和筛选相关信息。

适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
通过 npx skills add 命令从指定仓库安装，需结合原始 README 核验具体用法。
安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。
当前无额外底部简介，可参考来源仓库获取完整功能说明。

SKILL.md

Exa Search Skill

5 specialized scripts for Exa AI search API—neural search, content extraction, similar pages, research with citations, and async pro research.

Prerequisite: EXA_API_KEY environment variable. Get key at https://dashboard.exa.ai

Token-Efficient Search

Inspired by Anthropic's dynamic filtering—always filter before reasoning. ~24% fewer tokens, ~11% better accuracy.

The Principle: Search Cheaply → Filter → Extract Selectively → Reason

DO:

# Step 1: Search with --no-text (titles/URLs only — cheapest)
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" -n 20 --no-text

# Step 2: Evaluate titles, pick best 3-5 URLs

# Step 3: Extract only those URLs with bounded content
python3 ~/.claude/skills/exa-search/scripts/exa_contents.py URL1 URL2 --highlights --max-chars 3000

DON'T: Search with full text for 50 results, then reason over all of it.

Use API-Level Filters First (Free Filtering)

These reduce results at the API level before you ever see them:

--must-include "term" — results must contain this string
--must-exclude "term" — removes irrelevant results
--domains site1.com site2.com — restrict to authoritative sources
--category "research paper" — eliminate irrelevant content types
--after 2025-01-01 / --before — temporal filtering

Use Summaries Over Full Text

When you need the gist, not raw content:

# AI-distilled summaries — much smaller than full text
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --summary "Key findings" -n 5

Use Bounded Context for RAG

# Capped context string — prevents unbounded token usage
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --context --context-chars 5000

Post-Process with filter_web_results.py

Pipe Exa JSON output through the Firecrawl filter script for additional reduction:

python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --json | \
  python3 ~/.claude/skills/firecrawl/scripts/filter_web_results.py \
  --fields "title,url,text" --max-chars 3000

Cost Tiers — Match to Task

Type	Latency	Cost/1k	When
`--instant`	<150ms	Cheapest	Real-time lookups, autocomplete
`--fast`	~500ms	Low	Quick checks, confirmations
`auto` (default)	--	Medium	General search
`--deep`	4-12s	$12	Comprehensive research
`--deep-reasoning`	12-50s	$15	Maximum depth + synthesis

Structured Deep Search (Exa Deep)

Deep and deep-reasoning searches support structured JSON output via outputSchema. The API returns parsed content in output.content with per-field grounding citations and confidence scores.

Quick Example	Purpose
`... --deep --text-output "Short answer"`	Simple text answer
`... --deep-reasoning --schema-preset company`	Structured company research
`... --deep --output-schema '{"type":"object","properties":{"answer":{"type":"string"}}}'`	Custom schema
`... --deep --schema-file ~/schemas/analysis.json`	Schema from file

Presets: company, paper-survey, competitor-analysis, person, news-digest

Output includes field-level grounding: per-field citations with [H]igh/[M]edium/[L]ow confidence.

Available Scripts

1. exa_search.py — Neural Web Search

python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" [options]

Quick Example	Purpose
`... exa_search.py "AI frameworks"`	Basic search
`... exa_search.py "transformers" --category "research paper" -n 20`	Academic papers
`... exa_search.py "query" --deep --additional-queries "alt query"`	Deep search
`... exa_search.py "query" --domains docs.python.org`	Domain-filtered
`... exa_search.py "query" --after 2025-01-01 --category news`	Recent news
`... exa_search.py "query" --context --context-chars 10000`	RAG context
`... exa_search.py "query" --instant -n 5`	Sub-150ms lookup
`... exa_search.py "Top AI startups" --deep-reasoning --schema-preset company`	Structured company research
`... exa_search.py "Who is CEO of Stripe?" --deep --text-output "Short answer"`	Quick factual answer

Categories: company, research paper, news, pdf, github, tweet, personal site, people, financial report

2. exa_contents.py — URL Content Extraction

python3 ~/.claude/skills/exa-search/scripts/exa_contents.py URL [URL2...] [options]

Quick Example	Purpose
`... exa_contents.py "https://arxiv.org/abs/2307.06435"`	Extract paper
`... exa_contents.py URL --summary "Key methods" --highlights`	Summarized extraction
`... exa_contents.py URL --livecrawl always`	Fresh content
`... exa_contents.py URL --max-chars 5000`	Bounded extraction

3. exa_similar.py — Find Similar Pages

python3 ~/.claude/skills/exa-search/scripts/exa_similar.py URL [options]

Quick Example	Purpose
`... exa_similar.py "https://stripe.com" --category company --exclude-source`	Find competitors
`... exa_similar.py "https://arxiv.org/abs/..." -n 15`	Related papers
`... exa_similar.py URL --summary "How different?"`	Comparison summaries

4. exa_research.py — AI-Powered Research

python3 ~/.claude/skills/exa-search/scripts/exa_research.py "question" [options]

Quick Example	Purpose
`... exa_research.py "React vs Vue differences?" --sources`	Research with citations
`... exa_research.py "query" --stream`	Real-time streaming
`... exa_research.py "query" --domains docs.python.org`	Authoritative sources
`... exa_research.py "query" --markdown`	Markdown with citations
`... exa_research.py "query" --answer-only`	Pipe-friendly output

5. exa_research_async.py — Async Pro Research

python3 ~/.claude/skills/exa-search/scripts/exa_research_async.py "question" [options]

Quick Example	Purpose
`... exa_research_async.py "Compare AI frameworks" --pro --wait`	Pro model
`... exa_research_async.py "Quick overview" --fast`	Fast model
`... exa_research_async.py "query" --schema '{...}'`	Structured output
`... exa_research_async.py status r_abc123`	Check job
`... exa_research_async.py list`	List jobs

Script Selection Guide

Task	Best Script
Web search with filters	`exa_search.py`
Research papers	`exa_search.py --category "research paper"`
Company/startup info	`exa_search.py --category company`
GitHub repos/code	`exa_search.py --category github`
Extract known URL content	`exa_contents.py`
Find competitors	`exa_similar.py --exclude-source`
Quick answers with citations	`exa_research.py --sources`
Complex structured research	`exa_research_async.py --pro`
Real-time search	`exa_search.py --instant`
RAG context building	`exa_search.py --context`
Structured research with grounding	`exa_search.py --deep-reasoning --schema-preset company`
Quick factual answer	`exa_search.py --deep --text-output "Short answer"`

Exa vs Firecrawl vs Native Claude Tools

Need	Best Tool	Why
Semantic/neural search	Exa `exa_search.py`	AI-powered relevance
Find research papers	Exa `--category "research paper"`	Academic index
Quick research answer	Exa `exa_research.py`	Citations + synthesis
Find similar pages	Exa `exa_similar.py`	Semantic similarity
Single page → markdown	Firecrawl `scrape --only-main-content`	Cleanest output
Crawl entire site	Firecrawl `crawl --wait --progress`	Link following
Autonomous data finding	Firecrawl `agent`	No URLs needed
Search + scrape combined	Firecrawl `search --scrape`	One operation
Claude API agent building	Native `web_search_20260209`	Built-in dynamic filtering
Twitter/X content	`jina URL`	Only tool that works

Common Workflows

Research a Topic

python3 ~/.claude/skills/exa-search/scripts/exa_research.py "How does RAG work?" --sources --markdown

Literature Review

# Find papers, then find similar to best hit
python3 ~/.claude/skills/exa-search/scripts/exa_search.py "transformer optimization" --category "research paper" -n 20 --summary "Key contributions"
python3 ~/.claude/skills/exa-search/scripts/exa_similar.py "https://arxiv.org/abs/1706.03762" --category "research paper" -n 15

Documentation Research

python3 ~/.claude/skills/exa-search/scripts/exa_search.py "React useEffect cleanup" --domains react.dev developer.mozilla.org --context

Build RAG Context

python3 ~/.claude/skills/exa-search/scripts/exa_search.py "Python async patterns" --context --context-chars 15000 --domains docs.python.org

Reference Documentation

File	Contents
`references/exa-scripts-reference.md`	Full parameter reference for all 5 scripts, cost table, MCP comparison, test suite

Test Suite

python3 ~/.claude/skills/exa-search/scripts/test_exa.py --quick       # Quick validation
python3 ~/.claude/skills/exa-search/scripts/test_exa.py               # Full suite
python3 ~/.claude/skills/exa-search/scripts/test_exa.py --endpoint search  # Specific endpoint

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明，方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.22%

按下载量换算106

Claude

27.49%

按下载量换算81

Cursor

18.63%

按下载量换算55

Gemini CLI

9.51%

按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置，应进入高风险复核队列，默认不自动发布。

安装前确认

本站仅展示第三方公开信息，不托管安装包，不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果，不能写成本站确认安全。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/tdimino/claude-code-minoan

SKILL.md 来源

github.com

/tdimino/claude-code-minoan/tree/main/skills/exa-search

skills-sh

skills.sh

/tdimino/claude-code-minoan/exa-search

继续浏览同类 Skills

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上一个 Skill

exa-search（前搜索）

exa-search 用于查找、检索和筛选相关信息，适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。

下一个 Skill

exa-search-pro（exa 搜索专业版）

exa-search-pro 用于查找、检索和筛选相关信息，适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。