Claude-skill-registry elicitation-methodology
Hub skill for requirements elicitation. Provides technique selection, orchestration guidance, LLMREI patterns, and autonomy level configuration. Use when gathering requirements from stakeholders, conducting elicitation sessions, or preparing requirements for specification.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/elicitation-methodology" ~/.claude/skills/majiayu000-claude-skill-registry-elicitation-methodology && rm -rf "$T"
skills/data/elicitation-methodology/SKILL.mdElicitation Methodology
Central hub for requirements elicitation methodology, technique selection, and workflow orchestration.
When to Use This Skill
Keywords: requirements gathering, elicitation, stakeholder needs, requirement discovery, user needs, feature requests, interview, requirements session
Invoke this skill when:
- Starting a new requirements elicitation effort
- Selecting appropriate elicitation techniques
- Orchestrating multi-source elicitation
- Configuring autonomy levels for AI assistance
- Understanding LLMREI interview patterns
Quick Decision Tree
| Scenario | Recommended Approach |
|---|---|
| Have stakeholders to interview | Use skill |
| Have documents/PDFs to mine | Use skill |
| Working solo, need perspectives | Use skill |
| Need domain knowledge | Use skill |
| Checking completeness | Use skill |
| Ready for specification | Use command |
Elicitation Techniques
1. Stakeholder Interviews (LLMREI Pattern)
AI-conducted interviews using research-backed prompting strategies.
When to use:
- Direct access to stakeholders
- Complex domains requiring exploration
- Need to capture tacit knowledge
Technique reference: See
references/llmrei-patterns.md
2. Document Extraction
Mine requirements from existing documentation.
When to use:
- Existing requirements documents
- Meeting transcripts
- Regulatory documents
- Competitor analysis
Delegate to:
document-extraction skill
3. Stakeholder Simulation
Multi-persona simulation for solo requirements work.
When to use:
- Working without direct stakeholder access
- Need diverse perspectives
- Validating completeness
Delegate to:
stakeholder-simulation skill
4. Domain Research
MCP-powered research for domain knowledge.
When to use:
- Unfamiliar domain
- Need industry standards
- Competitive analysis
- Technology constraints
Delegate to:
domain-research skill
Autonomy Levels
Guided Mode (Human-in-Loop)
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
Semi-Autonomous Mode
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
Fully Autonomous Mode
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
Workflow Orchestration
Standard Discovery Workflow
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
Output Format
Pre-Canonical Requirements
# .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
Export Options
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
Related Skills
- Detailed LLMREI interview patternsinterview-conducting
- Document mining techniquesdocument-extraction
- Persona simulationstakeholder-simulation
- Completeness checkinggap-analysis
- MCP research coordinationdomain-research
References
- LLMREI prompting strategiesreferences/llmrei-patterns.md
- Technique selection guidancereferences/technique-matrix.md
- Detailed autonomy configurationreferences/autonomy-levels.md
Last Updated: 2025-12-26