Hub for selecting requirements elicitation techniques like interviews, document extraction, simulations, and research. Orchestrates workflows and configures AI autonomy levels for stakeholder sessions.
npx claudepluginhub melodic-software/claude-code-plugins --plugin requirements-elicitationThis skill is limited to using the following tools:
Central hub for requirements elicitation methodology, technique selection, and workflow orchestration.
Orchestrates requirements elicitation for a domain via interviews, document mining, simulations, research, gap analysis, and synthesis into unified YAML or other formats.
Elicits software requirements through stakeholder interviews, PRD structuring, scope definition, and user stories. Use for new projects, features, or specs from vague ideas.
Elicits requirements through structured questioning and generates high-quality SRS documents aligned with ISO/IEC/IEEE 29148 when no prior specs exist.
Share bugs, ideas, or general feedback.
Central hub for requirements elicitation methodology, technique selection, and workflow orchestration.
Keywords: requirements gathering, elicitation, stakeholder needs, requirement discovery, user needs, feature requests, interview, requirements session
Invoke this skill when:
| Scenario | Recommended Approach |
|---|---|
| Have stakeholders to interview | Use interview-conducting skill |
| Have documents/PDFs to mine | Use document-extraction skill |
| Working solo, need perspectives | Use stakeholder-simulation skill |
| Need domain knowledge | Use domain-research skill |
| Checking completeness | Use gap-analysis skill |
| Ready for specification | Use /export command |
AI-conducted interviews using research-backed prompting strategies.
When to use:
Technique reference: See references/llmrei-patterns.md
Mine requirements from existing documentation.
When to use:
Delegate to: document-extraction skill
Multi-persona simulation for solo requirements work.
When to use:
Delegate to: stakeholder-simulation skill
MCP-powered research for domain knowledge.
When to use:
Delegate to: domain-research skill
autonomy: guided
behavior:
- AI suggests questions, human approves
- Each requirement validated individually
- Human controls interview flow
- Maximum transparency
use_when:
- Sensitive or regulated domains
- Learning the elicitation process
- High-stakes requirements
autonomy: semi-auto
behavior:
- AI conducts interviews with checkpoints
- Human validates requirement batches
- Periodic progress reviews
- Balance of speed and control
use_when:
- Standard elicitation projects
- Moderate domain complexity
- Trusted AI capabilities
autonomy: full-auto
behavior:
- Complete end-to-end elicitation
- Human reviews final output only
- Maximum efficiency
- AI handles all decisions
use_when:
- Well-understood domains
- Time pressure
- Preliminary discovery
1. CONTEXT GATHERING
├── Load any existing business context
├── Identify available sources (stakeholders, docs, etc.)
└── Select autonomy level
2. MULTI-SOURCE ELICITATION
├── Interviews (if stakeholders available)
├── Document extraction (if docs available)
├── Domain research (MCP queries)
└── Stakeholder simulation (if solo mode)
3. SYNTHESIS
├── Consolidate requirements from all sources
├── Remove duplicates
├── Classify by type (functional, NFR, constraint)
└── Apply MoSCoW prioritization
4. VALIDATION
├── Gap analysis
├── Completeness checking
├── Conflict detection
└── INVEST scoring
5. OUTPUT
├── Save to .requirements/{domain}/
├── Generate summary report
└── Prepare for specification export
# .requirements/{domain}/requirements.yaml
id: REQ-SET-{number}
title: "{Domain} Requirements"
domain: "{domain-name}"
elicitation_date: "{ISO-8601-date}"
autonomy_level: "{guided|semi-auto|full-auto}"
sources:
- type: interview|document|simulation|research
reference: "{source-identifier}"
timestamp: "{ISO-8601-date}"
requirements:
- id: REQ-{number}
text: "{requirement statement}"
source: "{source-type}"
source_ref: "{specific-reference}"
priority: must|should|could|wont
category: functional|non-functional|constraint|assumption
confidence: high|medium|low
validation_status: pending|validated|rejected
gaps_identified:
- category: "{requirement-category}"
description: "{what's missing}"
severity: critical|major|minor
metadata:
total_sources: {number}
total_requirements: {number}
gap_count: {number}
ready_for_specification: true|false
After elicitation, requirements can be exported to various specification formats:
/requirements-elicitation:export --to canonical # Canonical spec format
/requirements-elicitation:export --to ears # EARS pattern format
/requirements-elicitation:export --to gherkin # Gherkin/BDD format
interview-conducting - Detailed LLMREI interview patternsdocument-extraction - Document mining techniquesstakeholder-simulation - Persona simulationgap-analysis - Completeness checkingdomain-research - MCP research coordinationreferences/llmrei-patterns.md - LLMREI prompting strategiesreferences/technique-matrix.md - Technique selection guidancereferences/autonomy-levels.md - Detailed autonomy configurationLast Updated: 2025-12-26