web-search 网页搜索中文使用指南 - Skill ZIP 下载与风险提示

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输出：按 Skill 说明生成的文档、代码、检查结果、计划、建议或操作步骤。

示例任务

安装方式

风险边界

使用前请检查权限、外部依赖和要处理的数据类型。第三方平台数据、支付、部署、账号和密钥相关内容应先核对官方说明。

SKILL.md 文档介绍

Web Search & Extraction

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

!Web Search & Extraction

Quick Start

> Requires inference.sh CLI (infsh). Get installation instructions: npx skills add inference-sh/skills@agent-tools

infsh login

# Search the web
infsh 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

infsh 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

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

Extracts clean text and images from multiple URLs.

Exa Search

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

Returns highly relevant links with context.

Exa Answer

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

Returns direct factual answers.

Exa Extract

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

Extracts and analyzes web page content.

Workflow: Research + LLM

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

# 2. Analyze with Claude
infsh 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
infsh app run tavily/extract --input '{
  "urls": ["https://example.com/long-article"]
}' > content.json

# 2. Summarize with LLM
infsh 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 150+ apps)
npx skills add inference-sh/skills@agent-tools

# 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: infsh 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

web-search 网页搜索

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适合任务

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