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English
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Chinese

Search Research

网页搜索研究

Find and synthesize information effectively.
高效地查找并整合信息。

When to use

适用场景

  • Deep research tasks
  • Fact verification
  • Competitive analysis
  • Documentation lookup
  • Trend analysis
  • 深度研究任务
  • 事实核查
  • 竞品分析
  • 文档查找
  • 趋势分析

Search strategies

搜索策略

Query formulation

查询语句构建

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Exact phrase

精确短语

"error handling best practices"
"error handling best practices"

Exclude terms

排除术语

python tutorial -beginner
python tutorial -beginner

Site-specific

指定站点

site:github.com react hooks
site:github.com react hooks

File type

指定文件类型

filetype:pdf security audit
filetype:pdf security audit

Date range (use WebSearch date filtering)

日期范围(使用WebSearch的日期筛选功能)

react 18 features 2024
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react 18 features 2024
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Domain filtering

域名过滤

python
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python
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WebSearch with domain filtering

带域名过滤的WebSearch

WebSearch( query="kubernetes best practices", allowed_domains=["kubernetes.io", "cloud.google.com", "docs.aws.amazon.com"], )
WebSearch( query="kubernetes best practices", allowed_domains=["kubernetes.io", "cloud.google.com", "docs.aws.amazon.com"], )

Exclude unreliable sources

排除不可靠来源

WebSearch( query="health benefits of X", blocked_domains=["pinterest.com", "quora.com"], )
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WebSearch( query="health benefits of X", blocked_domains=["pinterest.com", "quora.com"], )
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Research workflow

研究工作流

1. Scope definition

1. 范围定义

  • What specific question needs answering?
  • What type of sources are authoritative?
  • What time period is relevant?
  • 需要解答的具体问题是什么?
  • 哪些类型的来源具有权威性?
  • 相关的时间范围是?

2. Initial search

2. 初始搜索

python
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python
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Broad search first

先进行广泛搜索

queries = [ "main topic overview", "main topic best practices", "main topic common problems", ]
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queries = [ "main topic overview", "main topic best practices", "main topic common problems", ]
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3. Deep dive

3. 深度挖掘

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python
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Follow up on promising results

针对有价值的结果进行跟进

for result in initial_results: if is_authoritative(result): content = WebFetch(url=result.url, prompt="Extract key findings") facts.append(content)
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for result in initial_results: if is_authoritative(result): content = WebFetch(url=result.url, prompt="Extract key findings") facts.append(content)
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4. Verification

4. 验证

  • Cross-reference claims across sources
  • Check publication dates
  • Verify author credentials
  • Look for primary sources
  • 跨来源交叉验证主张
  • 检查发布日期
  • 核实作者资质
  • 查找原始来源

Output format

输出格式

markdown
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markdown
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Research Summary: [Topic]

研究摘要: [主题]

Key Findings

关键发现

  1. Finding 1 - Source
    • Supporting detail
    • Supporting detail
  2. Finding 2 - Source
    • Supporting detail
  1. 发现1 - 来源
    • 支持细节
    • 支持细节
  2. 发现2 - 来源
    • 支持细节

Consensus

共识

  • Points that multiple sources agree on
  • 多个来源达成一致的观点

Contradictions

矛盾点

  • Areas where sources disagree
  • 来源之间存在分歧的领域

Gaps

研究空白

  • Questions that couldn't be answered
  • 无法解答的问题

Sources

来源列表

  • Title - Credibility: High/Medium/Low
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  • 标题 - 可信度: 高/中/低
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Source evaluation

来源评估

IndicatorHigh CredibilityLow Credibility
Domain.gov, .edu, major publicationsUnknown, user-generated
AuthorNamed expert, organizationAnonymous, unclear
DateRecent, regularly updatedOutdated, no date
CitationsLinks to sourcesNo references
BiasBalanced, factualPromotional, extreme
指标高可信度低可信度
域名.gov、.edu、主流出版物未知域名、用户生成内容
作者知名专家、机构匿名、身份不明
日期近期更新、定期维护过时、无日期
引用有来源链接无参考资料
偏见客观中立、基于事实推广性质、极端观点

Examples

示例

Input: "Research best auth solutions for SaaS" Action: Search auth providers, compare features, check reviews, summarize
Input: "Verify this claim about performance" Action: Find benchmarks, check methodology, cross-reference results
输入: "研究SaaS的最佳身份验证解决方案" 操作: 搜索身份验证提供商、对比功能、查看评测、总结
输入: "验证关于性能的这一主张" 操作: 查找基准测试、检查方法论、交叉验证结果