AI-led stakeholder interviews using LLMREI research-backed patterns. Conducts structured interviews to elicit requirements through context-adaptive questioning, active listening, and systematic requirement extraction.
Conducts structured stakeholder interviews using research-backed LLMREI patterns. Triggers when you ask to interview stakeholders, elicit requirements, or gather user needs through conversation.
/plugin marketplace add melodic-software/claude-code-plugins/plugin install requirements-elicitation@melodic-softwareThis skill is limited to using the following tools:
references/interview-structure.mdreferences/question-pathways.mdAI-led stakeholder interviews using research-backed LLMREI patterns for effective requirements elicitation.
Keywords: stakeholder interview, requirements interview, LLMREI, elicit requirements, talk to stakeholder, interview session, user interview, customer interview
Invoke this skill when:
When interviewing an actual person through the chat interface:
mode: real_stakeholder
approach:
- Use AskUserQuestion tool for structured questions
- Allow natural conversation flow
- Adapt questions based on responses
- Summarize and confirm understanding periodically
When no real stakeholder is available:
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
Goals:
Questions:
Goals:
Question Types:
Goals:
Question Pathways:
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?"
Goals:
Techniques:
Goals:
General questions applicable to any interview:
| Question | Purpose |
|---|---|
| "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 |
Follow up on stakeholder responses to get specifics:
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?"
Introduce considerations the stakeholder may not have mentioned:
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]?"
As requirements emerge, capture them in this format:
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}"
| Mistake | Prevention |
|---|---|
| Very long questions | Keep questions concise and focused |
| Multiple unrelated questions | One question at a time |
| Leading questions | Use neutral language |
| Skipping NFRs | Explicitly ask about performance, security, usability |
| No summary | Recap periodically to verify understanding |
| Rushing | Allow silence; stakeholders often add important details |
After each interview, generate:
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}"
For specific techniques, delegate to:
references/llmrei-patterns.md from parent skillstakeholder-simulation skilldomain-research skill for backgroundSave interview results to:
.requirements/{domain}/interviews/INT-{number}.yaml
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