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interview-conducting

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Interview Conducting Skill

访谈执行Skill

AI-led stakeholder interviews using research-backed LLMREI patterns for effective requirements elicitation.
基于经研究验证的LLMREI模式，由AI主导利益相关者访谈，以高效获取需求。

When to Use This Skill

何时使用该Skill

Keywords: stakeholder interview, requirements interview, LLMREI, elicit requirements, talk to stakeholder, interview session, user interview, customer interview
Invoke this skill when:
  • Conducting a structured requirements interview with a stakeholder
  • Exploring user needs through conversation
  • Gathering requirements from subject matter experts
  • Clarifying and deepening understanding of requirements
关键词: stakeholder interview, requirements interview, LLMREI, elicit requirements, talk to stakeholder, interview session, user interview, customer interview
在以下场景调用该Skill：
  • 与利益相关者开展结构化需求访谈
  • 通过对话探索用户需求
  • 从领域专家处收集需求
  • 澄清并深化对需求的理解

Interview Modes

访谈模式

Real Stakeholder Interview

真实利益相关者访谈

When interviewing an actual person through the chat interface:
yaml
mode: real_stakeholder
approach:
  - Use AskUserQuestion tool for structured questions
  - Allow natural conversation flow
  - Adapt questions based on responses
  - Summarize and confirm understanding periodically
当通过聊天界面访谈真实人员时：
yaml
mode: real_stakeholder
approach:
  - Use AskUserQuestion tool for structured questions
  - Allow natural conversation flow
  - Adapt questions based on responses
  - Summarize and confirm understanding periodically

Simulated Interview (Solo Mode)

模拟访谈（单人模式）

When no real stakeholder is available:
yaml
mode: simulated
approach:
  - Spawn persona agent via Task tool
  - Conduct interview with simulated stakeholder
  - Mark requirements with lower confidence
  - Flag items needing real stakeholder validation
当没有真实利益相关者可用时：
yaml
mode: simulated
approach:
  - Spawn persona agent via Task tool
  - Conduct interview with simulated stakeholder
  - Mark requirements with lower confidence
  - Flag items needing real stakeholder validation

Interview Structure (LLMREI Pattern)

访谈结构（LLMREI模式）

Phase 1: Opening (2-3 minutes)

阶段1：开场（2-3分钟）

Goals:
  • Establish rapport
  • Set expectations
  • Explain the process
Questions:
  • "Thank you for your time. Could you briefly describe your role and how you interact with this project?"
  • "What outcomes would make this interview successful for you?"
目标:
  • 建立融洽关系
  • 设定预期
  • 说明流程
问题:
  • "感谢您抽出时间。能否简要介绍您的角色以及您与该项目的互动方式？"
  • "您认为本次访谈取得成功的标志是什么？"

Phase 2: Context Gathering (5-10 minutes)

阶段2：情境收集（5-10分钟）

Goals:
  • Understand stakeholder perspective
  • Identify key concerns
  • Map relationships
Question Types:
  • Role-based: "How does your team currently handle X?"
  • Priority-based: "What are your top three concerns about this project?"
  • Relationship-based: "Who else should we talk to about X?"
目标:
  • 理解利益相关者的视角
  • 识别关键关注点
  • 梳理关系网络
问题类型:
  • 角色相关："您的团队目前如何处理X？"
  • 优先级相关："您对该项目的三大核心顾虑是什么？"
  • 关系相关："关于X，我们还应该与哪些人沟通？"

Phase 3: Requirements Exploration (15-25 minutes)

阶段3：需求探索（15-25分钟）

Goals:
  • Elicit functional requirements
  • Identify non-functional requirements
  • Uncover constraints and assumptions
Question Pathways:
text
Start with open-ended → Follow up with specifics → Validate understanding

Example:
Q1: "What should the system do when a user logs in?"
Q2: "You mentioned 'quick access to dashboard' - what does quick mean to you?"
Q3: "So the login should complete in under 2 seconds and show the dashboard. Is that right?"
目标:
  • 获取功能性需求
  • 识别非功能性需求
  • 发现约束条件与假设前提
问题路径:
text
Start with open-ended → Follow up with specifics → Validate understanding

Example:
Q1: "What should the system do when a user logs in?"
Q2: "You mentioned 'quick access to dashboard' - what does quick mean to you?"
Q3: "So the login should complete in under 2 seconds and show the dashboard. Is that right?"

Phase 4: Validation (5-10 minutes)

阶段4：验证确认（5-10分钟）

Goals:
  • Summarize key requirements
  • Verify understanding
  • Identify gaps
Techniques:
  • Read back requirements for confirmation
  • Ask "What have we missed?"
  • Prioritize using MoSCoW
目标:
  • 总结关键需求
  • 验证理解的准确性
  • 识别信息缺口
技巧:
  • 复述需求以获取确认
  • 询问"我们遗漏了什么？"
  • 使用MoSCoW方法划分优先级

Phase 5: Closing (2-3 minutes)

阶段5：收尾（2-3分钟）

Goals:
  • Thank stakeholder
  • Explain next steps
  • Offer follow-up
目标:
  • 感谢利益相关者
  • 说明后续步骤
  • 提供跟进渠道

Question Types

问题类型

Context-Independent Questions

通用情境问题

General questions applicable to any interview:
QuestionPurpose
"What is your primary goal for this system?"High-level vision
"Who are the main users?"User identification
"What existing systems does this replace/integrate with?"Context mapping
"What would failure look like?"Risk identification
适用于任何访谈的通用问题：
问题目的
"该系统的核心目标是什么？"明确高层愿景
"主要用户群体有哪些？"识别用户群体
"该系统将替代/集成哪些现有系统？"梳理情境关联
"失败的场景是什么样的？"识别风险点

Context-Deepening Questions

情境深挖问题

Follow up on stakeholder responses to get specifics:
text
Pattern: [Stakeholder says X] → "When you say X, what specifically do you mean?"

Examples:
- "fast" → "What response time are you expecting? Under 1 second?"
- "secure" → "What specific security requirements apply? Authentication methods?"
- "easy to use" → "Can you describe what easy means? Any specific workflows?"
针对利益相关者的回复进行跟进以获取具体信息：
text
Pattern: [Stakeholder says X] → "When you say X, what specifically do you mean?"

Examples:
- "fast" → "What response time are you expecting? Under 1 second?"
- "secure" → "What specific security requirements apply? Authentication methods?"
- "easy to use" → "Can you describe what easy means? Any specific workflows?"

Context-Enhancing Questions

情境拓展问题

Introduce considerations the stakeholder may not have mentioned:
text
Pattern: Suggest possibilities based on domain knowledge

Examples:
- "Have you considered how this works on mobile devices?"
- "What happens if the user loses connectivity mid-operation?"
- "How should the system handle peak load during [known busy period]?"
提出利益相关者可能未提及的考量点：
text
Pattern: Suggest possibilities based on domain knowledge

Examples:
- "Have you considered how this works on mobile devices?"
- "What happens if the user loses connectivity mid-operation?"
- "How should the system handle peak load during [known busy period]?"

Requirement Extraction

需求提取

As requirements emerge, capture them in this format:
yaml
requirement:
  id: REQ-{number}
  text: "{requirement statement}"
  source: interview
  stakeholder: "{role}"
  timestamp: "{ISO-8601}"
  type: functional|non-functional|constraint
  priority: must|should|could|wont
  confidence: high|medium|low
  raw_quote: "{exact stakeholder words if notable}"
当需求浮现时，按以下格式记录：
yaml
requirement:
  id: REQ-{number}
  text: "{requirement statement}"
  source: interview
  stakeholder: "{role}"
  timestamp: "{ISO-8601}"
  type: functional|non-functional|constraint
  priority: must|should|could|wont
  confidence: high|medium|low
  raw_quote: "{exact stakeholder words if notable}"

Common Mistakes to Avoid

需避免的常见错误

MistakePrevention
Very long questionsKeep questions concise and focused
Multiple unrelated questionsOne question at a time
Leading questionsUse neutral language
Skipping NFRsExplicitly ask about performance, security, usability
No summaryRecap periodically to verify understanding
RushingAllow silence; stakeholders often add important details
错误预防措施
问题过长保持问题简洁聚焦
一次提出多个不相关问题一次只问一个问题
诱导性问题使用中立语言
忽略非功能性需求（NFRs）明确询问性能、安全性、易用性等方面
不做总结定期复述以验证理解
节奏过快允许沉默；利益相关者往往会补充重要细节

Interview Summary Template

访谈总结模板

After each interview, generate:
yaml
interview_summary:
  session_id: "INT-{number}"
  stakeholder_role: "{role}"
  duration_minutes: {number}
  date: "{ISO-8601}"
  autonomy_level: "{guided|semi-auto|full-auto}"

  key_themes:
    - "{theme-1}"
    - "{theme-2}"

  requirements_elicited:
    - id: REQ-{number}
      text: "{requirement}"
      confidence: high|medium|low
      type: functional|non-functional|constraint
      priority: must|should|could

  follow_up_needed:
    - "{question or topic needing clarification}"

  stakeholder_quotes:
    - "{notable direct quote}"

  observations:
    - "{interviewer observation about needs or concerns}"

  next_steps:
    - "{recommended action}"
每次访谈后，生成以下内容：
yaml
interview_summary:
  session_id: "INT-{number}"
  stakeholder_role: "{role}"
  duration_minutes: {number}
  date: "{ISO-8601}"
  autonomy_level: "{guided|semi-auto|full-auto}"

  key_themes:
    - "{theme-1}"
    - "{theme-2}"

  requirements_elicited:
    - id: REQ-{number}
      text: "{requirement}"
      confidence: high|medium|low
      type: functional|non-functional|constraint
      priority: must|should|could

  follow_up_needed:
    - "{question or topic needing clarification}"

  stakeholder_quotes:
    - "{notable direct quote}"

  observations:
    - "{interviewer observation about needs or concerns}"

  next_steps:
    - "{recommended action}"

Delegation

任务委派

For specific techniques, delegate to:
  • LLMREI patterns: Load 
    references/llmrei-patterns.md
    from parent skill
  • Stakeholder simulation: Invoke 
    stakeholder-simulation
    skill
  • Domain research: Invoke 
    domain-research
    skill for background
针对特定技术，可委派至：
  • LLMREI模式: 从父Skill加载
    references/llmrei-patterns.md
  • 利益相关者模拟: 调用
    stakeholder-simulation
    Skill
  • 领域研究: 调用
    domain-research
    Skill获取背景信息

Output Location

输出位置

Save interview results to:
text
.requirements/{domain}/interviews/INT-{number}.yaml
将访谈结果保存至：
text
.requirements/{domain}/interviews/INT-{number}.yaml

Related

相关技能

  • elicitation-methodology
    - Parent hub skill
  • stakeholder-simulation
    - For simulated interviews
  • gap-analysis
    - Post-interview completeness checking
  • elicitation-methodology
    - 父级核心Skill
  • stakeholder-simulation
    - 用于模拟访谈
  • gap-analysis
    - 访谈后完整性检查