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

yaml

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

yaml

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

yaml

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:

yaml

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:

yaml

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:

yaml

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:

yaml

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:

yaml

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

yaml

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

yaml

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

yaml

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

yaml

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

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

Effective Firecrawl Queries

yaml

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:

yaml

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:

text

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

elicitation-methodology - Parent hub skill
gap-analysis - Research to fill gaps
interview-conducting - Validate research findings

Last Updated: 2025-12-29

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SKILL.md

Domain Research Skill

MANDATORY: Documentation-First Approach

When to Use This Skill

Available MCP Servers

Perplexity (General Research)

Context7 (Library Documentation)

Firecrawl (Web Scraping)

Research Patterns

Pattern 1: Domain Background

Pattern 2: Best Practices

Pattern 3: Competitive Analysis

Pattern 4: Regulatory Research

Pattern 5: Technology Constraints

Research Workflow

Step 1: Define Research Scope

Step 2: Execute Research Queries

Step 3: Synthesize Findings

Step 4: Document Results

Output Format

Research Results

Query Optimization

Effective Perplexity Queries

Effective Context7 Queries

Effective Firecrawl Queries

Confidence Levels

Delegation

Output Location

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