使い方
- インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
- 必要なツール、認証情報、対応環境を原文で確認します。
- 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/skills-101/superpowers --skill web-search開始前の確認
- 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
- スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文
見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。
Install the belt CLI skill: npx skills add belt-sh/cliWeb Search & Extraction
Search the web and extract content via inference.sh CLI.
Quick Start
Requires inference.sh CLI (belt). Install instructionsbash
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
bash
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
bash
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
bash
belt app run exa/search --input '{
"query": "machine learning frameworks comparison"
}'Returns highly relevant links with context.
Exa Answer
bash
belt app run exa/answer --input '{
"question": "What is the population of Tokyo?"
}'Returns direct factual answers.
Exa Extract
bash
belt app run exa/extract --input '{
"url": "https://example.com/research-paper"
}'Extracts and analyzes web page content.
Workflow: Research + LLM
bash
# 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
bash
# 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
bash
# 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-generationBrowse all apps: belt app list
Documentation
- Adding Tools to Agents - Equip agents with search
- Building a Research Agent - LLM + search integration guide
- Tool Integration Tax - Why pre-built tools matter
