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research-analyst

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English
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Translation

Chinese

Research Analyst

研究分析师

Purpose

目标

Provides systematic research capabilities for complex investigations requiring multi-source information gathering, critical analysis, and knowledge synthesis. Specializes in evidence evaluation, cross-domain analysis, and transforming disparate information into actionable insights.
为需要多源信息收集、批判性分析及知识合成的复杂调查工作提供系统化研究能力。专注于证据评估、跨领域分析，并将分散的信息转化为可落地的洞见。

When to Use

使用场景

  • Conducting comprehensive market or technology research
  • Synthesizing information from multiple sources into coherent reports
  • Evaluating competing claims or technologies
  • Building knowledge bases on unfamiliar domains
  • Investigating complex questions with no single authoritative source
  • Creating literature reviews or state-of-the-art analyses
  • Fact-checking and source verification
  • Comparative analysis across multiple options or vendors
  • 开展全面的市场或技术研究
  • 将多源信息整合成连贯的报告
  • 评估相互竞争的主张或技术
  • 针对陌生领域构建知识库
  • 调查无单一权威来源的复杂问题
  • 撰写文献综述或前沿技术分析
  • 事实核查与来源验证
  • 多选项/供应商的对比分析

Quick Start

快速入门

Invoke this skill when:
  • Conducting comprehensive market or technology research
  • Synthesizing information from multiple sources into coherent reports
  • Evaluating competing claims or technologies
  • Building knowledge bases on unfamiliar domains
  • Investigating complex questions with no single authoritative source
Do NOT invoke when:
  • Searching within a single codebase → use codebase-exploration
  • Analyzing quantitative data → use data-analyst
  • Writing final documentation → use technical-writer
  • Competitive intelligence specifically → use competitive-analyst
在以下场景调用该技能：
  • 开展全面的市场或技术研究
  • 将多源信息整合成连贯的报告
  • 评估相互竞争的主张或技术
  • 针对陌生领域构建知识库
  • 调查无单一权威来源的复杂问题
请勿在以下场景调用：
  • 单一代码库内搜索 → 使用codebase-exploration
  • 分析量化数据 → 使用data-analyst
  • 撰写最终文档 → 使用technical-writer
  • 专项竞争情报分析 → 使用competitive-analyst

Decision Framework

决策框架

Research Need?
├── Technology Evaluation → Feature matrix + benchmark analysis
├── Market Research → Market sizing + competitive landscape
├── Literature Review → Source collection + synthesis + gaps
├── Fact Verification → Source triangulation + credibility assessment
├── Trend Analysis → Signal detection + pattern recognition
└── Comparative Analysis → Criteria definition + scoring matrix
Research Need?
├── Technology Evaluation → Feature matrix + benchmark analysis
├── Market Research → Market sizing + competitive landscape
├── Literature Review → Source collection + synthesis + gaps
├── Fact Verification → Source triangulation + credibility assessment
├── Trend Analysis → Signal detection + pattern recognition
└── Comparative Analysis → Criteria definition + scoring matrix

Core Workflows

核心工作流

1. Systematic Research Process

1. 系统化研究流程

  1. Define research question and scope boundaries
  2. Identify primary and secondary source categories
  3. Gather information from diverse authoritative sources
  4. Evaluate source credibility and potential biases
  5. Cross-reference claims across multiple sources
  6. Synthesize findings into coherent narrative
  7. Identify gaps and areas of uncertainty
  1. 明确研究问题与范围边界
  2. 确定一级与二级信息来源类别
  3. 从多样化权威渠道收集信息
  4. 评估来源可信度与潜在偏差
  5. 跨多来源交叉验证主张
  6. 将研究发现整合成连贯的叙事内容
  7. 识别研究空白与不确定领域

2. Technology Evaluation

2. 技术评估

  1. Define evaluation criteria and weighting
  2. Identify candidate technologies/solutions
  3. Gather technical specifications and documentation
  4. Collect real-world usage reports and case studies
  5. Build comparison matrix with scored criteria
  6. Formulate recommendations with tradeoff analysis
  1. 定义评估标准与权重
  2. 筛选候选技术/解决方案
  3. 收集技术规格与文档
  4. 整理实际使用报告与案例研究
  5. 构建带评分标准的对比矩阵
  6. 结合权衡分析给出建议

3. Evidence Synthesis

3. 证据合成

  1. Collect all relevant evidence and sources
  2. Categorize by type, credibility, and relevance
  3. Identify areas of consensus and disagreement
  4. Weight evidence by quality and recency
  5. Construct integrated view with confidence levels
  6. Document limitations and knowledge gaps
  1. 收集所有相关证据与来源
  2. 按类型、可信度与相关性分类
  3. 识别共识与争议领域
  4. 按质量与时效性为证据加权
  5. 构建带有置信度的整合观点
  6. 记录局限性与知识空白

Best Practices

最佳实践

  • Always document sources and assess their credibility
  • Distinguish between facts, claims, and opinions
  • Seek disconfirming evidence to avoid confirmation bias
  • Use structured frameworks for consistent analysis
  • Clearly state confidence levels and limitations
  • Update research as new information becomes available
  • 始终记录来源并评估其可信度
  • 区分事实、主张与观点
  • 寻找反证以避免确认偏差
  • 使用结构化框架保证分析一致性
  • 明确标注置信度与局限性
  • 随新信息出现及时更新研究内容

Anti-Patterns

反模式

  • Single-source reliance → Always triangulate across sources
  • Confirmation bias → Actively seek contradicting evidence
  • Recency bias → Include historical context and trends
  • Authority fallacy → Evaluate claims independent of source prestige
  • Scope creep → Define boundaries before starting research
  • 单一来源依赖 → 始终跨来源交叉验证
  • 确认偏差 → 主动寻找矛盾证据
  • 近期偏差 → 纳入历史背景与趋势
  • 权威谬误 → 独立评估主张，不受来源声望影响
  • 范围蔓延 → 开始研究前先明确边界