web-search

作成者： 101-skills

TavilyとExaを使用したウェブ検索とコンテンツ抽出（inference.sh CLI経由）。アプリ：Tavily Search、Tavily Extract、Exa Search、Exa Answer、Exa Extract。機能：AI駆動検索、コンテンツ抽出、直接回答、リサーチ。用途：リサーチ、RAGパイプライン、ファクトチェック、コンテンツ集約、エージェント。トリガー：ウェブ検索、tavily、exa、search api、コンテンツ抽出、リサーチ、インターネット検索、ai検索、検索アシスタント、ウェブスクレイピング、rag、perplexity代替

npx skills add https://github.com/101-skills/skills --skill web-search

ZIPダウンロード GitHub

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このスキルを試すスポンサー

Install the belt CLI skill: npx skills add belt-sh/cli

Web Search & Extraction

Search the web and extract content via inference.sh CLI.

Web Search & Extraction

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

# Search the web
belt app run tavily/search-assistant --input '{"query": "latest AI developments 2024"}'

Available Apps

Tavily

App	App ID	Description
Search Assistant	`tavily/search-assistant`	AI-powered search with answers
Extract	`tavily/extract`	Extract content from URLs

Exa

App	App ID	Description
Search	`exa/search`	Smart web search with AI
Answer	`exa/answer`	Direct factual answers
Extract	`exa/extract`	Extract and analyze web content

Examples

Tavily Search

belt app run tavily/search-assistant --input '{
  "query": "What are the best practices for building AI agents?"
}'

Returns AI-generated answers with sources and images.

Tavily Extract

belt app run tavily/extract --input '{
  "urls": ["https://example.com/article1", "https://example.com/article2"]
}'

Extracts clean text and images from multiple URLs.

Exa Search

belt app run exa/search --input '{
  "query": "machine learning frameworks comparison"
}'

Returns highly relevant links with context.

Exa Answer

belt app run exa/answer --input '{
  "question": "What is the population of Tokyo?"
}'

Returns direct factual answers.

Exa Extract

belt app run exa/extract --input '{
  "url": "https://example.com/research-paper"
}'

Extracts and analyzes web page content.

Workflow: Research + LLM

# 1. Search for information
belt app run tavily/search-assistant --input '{
  "query": "latest developments in quantum computing"
}' > search_results.json

# 2. Analyze with Claude
belt app run openrouter/claude-sonnet-45 --input '{
  "prompt": "Based on this research, summarize the key trends: <search-results>"
}'

Workflow: Extract + Summarize

# 1. Extract content from URL
belt app run tavily/extract --input '{
  "urls": ["https://example.com/long-article"]
}' > content.json

# 2. Summarize with LLM
belt app run openrouter/claude-haiku-45 --input '{
  "prompt": "Summarize this article in 3 bullet points: <content>"
}'

Use Cases

Research: Gather information on any topic
RAG: Retrieval-augmented generation
Fact-checking: Verify claims with sources
Content aggregation: Collect data from multiple sources
Agents: Build research-capable AI agents

Related Skills

# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli

# LLM models (combine with search for RAG)
npx skills add inference-sh/skills@llm-models

# Image generation
npx skills add inference-sh/skills@ai-image-generation

Browse all apps: belt app list