Domain Research Skill

MCP-powered domain research for enriching requirements elicitation with external knowledge.

MANDATORY: Documentation-First Approach

Before conducting domain research:

• Invoke docs-management skill for requirements elicitation patterns

• Use MCP servers as primary research tools (perplexity, context7, firecrawl)

• Base all guidance on official documentation and authoritative sources

When to Use This Skill

Keywords: domain research, MCP research, industry standards, best practices, competitive analysis, technology research, regulatory requirements

Invoke this skill when:

• Unfamiliar with a domain and need background

• Researching industry standards and best practices

• Investigating regulatory requirements

• Analyzing competitor features

• Exploring technology constraints

• Supplementing stakeholder knowledge

Available MCP Servers

Perplexity (General Research)

Use for:

• Industry best practices

• Recent developments

• Comparative analysis

• Regulatory overviews

mcp_tool: mcp__perplexity__search example_queries:

• "e-commerce checkout best practices 2025"
• "GDPR compliance requirements for SaaS"
• "authentication patterns for financial applications"

Context7 (Library Documentation)

Use for:

• Framework requirements

• API constraints

• Library capabilities

• Technical limitations

mcp_tools:

• mcp__context7__resolve-library-id
• mcp__context7__query-docs example_queries:
• Library: "react" → Query: "state management patterns"
• Library: "fastapi" → Query: "authentication requirements"

Firecrawl (Web Scraping)

Use for:

• Competitor analysis

• Documentation extraction

• Feature comparison

• Market research

mcp_tools:

• mcp__firecrawl__firecrawl_search
• mcp__firecrawl__firecrawl_scrape example_queries:
• Search: "inventory management software features"
• Scrape: Competitor feature pages

Research Patterns

Pattern 1: Domain Background

Build foundational domain knowledge:

research_pattern: domain_background steps:

1. Use perplexity for industry overview
2. Identify key concepts and terminology
3. Research common requirements in domain
4. Note regulatory considerations output: Domain context document

Pattern 2: Best Practices

Research current best practices:

research_pattern: best_practices steps:

1. Search for "best practices" in domain
2. Filter for recent (last 2 years)
3. Identify common patterns
4. Note recommended approaches output: Best practices summary

Pattern 3: Competitive Analysis

Research competitor features:

research_pattern: competitive_analysis steps:

1. Identify key competitors
2. Scrape feature pages with firecrawl
3. Extract capability lists
4. Compare and contrast output: Competitive feature matrix

Pattern 4: Regulatory Research

Research compliance requirements:

research_pattern: regulatory steps:

1. Identify applicable regulations
2. Research specific requirements
3. Note mandatory vs recommended
4. Document compliance criteria output: Regulatory requirements list

Pattern 5: Technology Constraints

Research technical requirements:

research_pattern: technology steps:

1. Identify technologies in scope
2. Use context7 for library docs
3. Research integration requirements
4. Document technical constraints output: Technical requirements document

Research Workflow

Step 1: Define Research Scope

research_scope: domain: "{domain name}" topic: "{specific focus area}" depth: shallow|moderate|deep sources: [perplexity, context7, firecrawl]

Step 2: Execute Research Queries

For each research need:

• Select appropriate MCP server

• Formulate effective query

• Process results

• Extract requirements

Step 3: Synthesize Findings

Combine research into actionable requirements:

• Identify common patterns

• Note conflicts or options

• Highlight mandatory items

• Suggest priorities

Step 4: Document Results

Save research findings and derived requirements.

Output Format

Research Results

research_session: id: "RES-{timestamp}" domain: "{domain}" topic: "{research topic}" timestamp: "{ISO-8601}"

queries_executed: - server: perplexity query: "{query text}" results_count: {number}

- server: firecrawl
  url: "{scraped URL}"
  content_type: feature_page

findings: domain_context: - "{key finding 1}" - "{key finding 2}"

best_practices:
  - "{recommended practice 1}"
  - "{recommended practice 2}"

regulatory:
  - regulation: "GDPR"
    requirements:
      - "{requirement 1}"
      - "{requirement 2}"

competitive:
  - competitor: "{name}"
    features:
      - "{feature 1}"
      - "{feature 2}"

derived_requirements: - id: REQ-RES-001 text: "{requirement statement}" source: research source_detail: "{where this came from}" confidence: low # Research-derived = low confidence needs_validation: true category: "{category}"

recommendations: - topic: "{topic}" finding: "{what research showed}" implication: "{what this means for requirements}"

gaps_in_research: - "{area where more research needed}"

Query Optimization

Effective Perplexity Queries

query_patterns: best_practices: template: "{domain} {topic} best practices {year}" example: "e-commerce checkout best practices 2025"

requirements: template: "{domain} {topic} requirements specifications" example: "healthcare application HIPAA requirements"

comparison: template: "{topic A} vs {topic B} for {use case}" example: "OAuth 2.0 vs SAML for enterprise SSO"

regulatory: template: "{regulation} requirements for {industry}" example: "PCI-DSS requirements for payment processing"

Effective Context7 Queries

query_patterns: library_features: resolve: "{library name}" get_docs: topic="{specific feature}"

integration: resolve: "{library name}" get_docs: topic="integration authentication"

Effective Firecrawl Queries

query_patterns: competitor_features: search: "{competitor} features {product type}" scrape: Feature page URLs

documentation: search: "{technology} documentation requirements" scrape: Official docs

Confidence Levels

Research-derived requirements have inherent confidence limits:

confidence_levels: high: sources: [official documentation, regulatory text] note: "Verified from authoritative source"

medium: sources: [industry articles, best practice guides] note: "Generally accepted but verify with stakeholders"

low: sources: [competitor analysis, general web] note: "Use as starting point, requires validation"

Delegation

For follow-up actions:

• interview-conducting: Validate research with stakeholders

• gap-analysis: Check research fills identified gaps

• elicitation-methodology: Return for technique selection

Output Location

Save research results to:

.requirements/{domain}/research/RES-{timestamp}.yaml

Related

• elicitation-methodology

• Parent hub skill

• gap-analysis

• Research to fill gaps

• interview-conducting

• Validate research findings

Last Updated: 2025-12-29