elicitation-methodology

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Translated

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.

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npx skill4agent add melodic-software/claude-code-plugins elicitation-methodology

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Translated version includes tags in frontmatter
requirements-elicitationworkflow-orchestrationautonomy-configurationllmrei-patternsstakeholder-management

SKILL.md Content

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Elicitation 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

ScenarioRecommended Approach
Have stakeholders to interviewUse 
interview-conducting
skill
Have documents/PDFs to mineUse 
document-extraction
skill
Working solo, need perspectivesUse 
stakeholder-simulation
skill
Need domain knowledgeUse 
domain-research
skill
Checking completenessUse 
gap-analysis
skill
Ready for specificationUse 
/export
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)

yaml
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

yaml
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

yaml
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

text
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

yaml
# .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:
bash
/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

  • interview-conducting
    - Detailed LLMREI interview patterns
  • document-extraction
    - Document mining techniques
  • stakeholder-simulation
    - Persona simulation
  • gap-analysis
    - Completeness checking
  • domain-research
    - MCP research coordination

References

  • references/llmrei-patterns.md
    - LLMREI prompting strategies
  • references/technique-matrix.md
    - Technique selection guidance
  • references/autonomy-levels.md
    - Detailed autonomy configuration
Last Updated: 2025-12-26