Research Command Skill | Agent Skills

Research Command

Research domain knowledge using MCP servers to enrich requirements elicitation.

Usage

/requirements-elicitation:research "e-commerce checkout best practices"
/requirements-elicitation:research "GDPR compliance" --domain "user-data" --depth deep
/requirements-elicitation:research "authentication patterns" --focus regulatory
/requirements-elicitation:research "competitor features" --focus competitive

Arguments

| Argument | Required | Description | |----------|----------|-------------| | topic | Yes | The topic to research | | --domain | No | Domain name for organizing output | | --depth | No | Research depth: shallow, moderate, deep (default: moderate) | | --focus | No | Research focus: best-practices, regulatory, competitive, technical, all |

Research Capabilities

Best Practices Research

Industry standards
Common patterns
Recommended approaches
Lessons learned

Regulatory Research

Compliance requirements
Legal obligations
Industry regulations
Audit requirements

Competitive Research

Competitor features
Market standards
Differentiation opportunities
Feature gaps

Technical Research

Library capabilities
Framework requirements
Integration patterns
Technology constraints

Workflow

Step 1: Parse Research Request

research_request:
  topic: "{from argument}"
  domain: "{from --domain}"
  depth: shallow|moderate|deep
  focus: "{from --focus or all}"

Step 2: Load Domain Research Skill

Invoke the requirements-elicitation:domain-research skill to load MCP patterns.

Step 3: Execute MCP Queries

Based on focus area:

Best Practices:

queries:
  - server: perplexity
    query: "{topic} best practices 2025"
  - server: perplexity
    query: "{topic} common patterns recommendations"

Regulatory:

queries:
  - server: perplexity
    query: "{regulation} requirements {industry}"
  - server: firecrawl
    action: scrape regulatory documentation

Competitive:

queries:
  - server: firecrawl
    action: search competitor features
  - server: perplexity
    query: "{industry} market leaders features"

Technical:

queries:
  - server: context7
    action: resolve library, get docs
  - server: perplexity
    query: "{technology} integration requirements"

Step 4: Synthesize Findings

Combine research results:

Extract key findings
Identify requirements implications
Note confidence levels
Flag items needing validation

Step 5: Save and Report

Save to .requirements/{domain}/research/ Display summary of findings.

Examples

Best Practices Research

/requirements-elicitation:research "e-commerce checkout optimization"

Output:

Researching: e-commerce checkout optimization
Depth: moderate
Focus: best-practices

Querying MCP servers...
  [perplexity] e-commerce checkout best practices 2025
  [perplexity] cart abandonment reduction techniques

Key Findings:

1. CHECKOUT FLOW
   - Guest checkout reduces abandonment by 30%
   - Progress indicators increase completion
   - Mobile-first design essential

2. PAYMENT
   - Multiple payment options required
   - Saved payment methods increase conversion
   - Clear security indicators build trust

3. PERFORMANCE
   - Checkout should complete in < 3 steps
   - Page load < 2 seconds critical
   - Real-time validation reduces errors

Derived Requirements (8):
  REQ-RES-001: System shall support guest checkout
  REQ-RES-002: System shall display checkout progress
  REQ-RES-003: System shall support multiple payment methods
  REQ-RES-004: System shall complete checkout in 3 steps or fewer
  ... (4 more)

Confidence: MEDIUM (needs stakeholder validation)

Saved to: .requirements/checkout/research/RES-20251225-170000.yaml

Regulatory Research

/requirements-elicitation:research "PCI-DSS" --focus regulatory --depth deep

Output:

Researching: PCI-DSS compliance
Depth: deep
Focus: regulatory

Querying MCP servers...
  [perplexity] PCI-DSS requirements payment processing
  [perplexity] PCI-DSS 4.0 changes requirements
  [firecrawl] scraping PCI Security Standards Council

Key Findings:

1. DATA PROTECTION (Requirement 3)
   - Never store CVV after authorization
   - Encrypt stored card data (AES-256)
   - Mask PAN when displayed

2. ACCESS CONTROL (Requirement 7-8)
   - Restrict access to need-to-know
   - Unique IDs for each user
   - MFA for administrative access

3. MONITORING (Requirement 10)
   - Log all access to cardholder data
   - Retain logs for 1 year minimum
   - Daily log review required

4. TESTING (Requirement 11)
   - Quarterly vulnerability scans
   - Annual penetration testing
   - Change detection mechanisms

Derived Requirements (15):
  REQ-RES-001: System shall not store CVV/CVC after authorization [MUST]
  REQ-RES-002: System shall encrypt stored card data using AES-256 [MUST]
  REQ-RES-003: System shall mask PAN displaying only last 4 digits [MUST]
  ... (12 more)

Confidence: HIGH (from official documentation)

Saved to: .requirements/payment/research/RES-20251225-171500.yaml

Competitive Research

/requirements-elicitation:research "inventory management software" --focus competitive

Output:

Researching: inventory management software competitors
Depth: moderate
Focus: competitive

Querying MCP servers...
  [firecrawl] searching inventory management software features
  [perplexity] inventory management market leaders 2025

Competitors Analyzed:

1. CompetitorA
   - Real-time inventory tracking
   - Multi-warehouse support
   - Barcode scanning
   - Automated reorder points

2. CompetitorB
   - AI demand forecasting
   - Supplier management
   - Integration marketplace
   - Mobile app

3. CompetitorC
   - Simple interface
   - Low-cost option
   - Basic reporting
   - Limited integrations

Feature Matrix:
  Feature               | A | B | C | Our Need?
  Real-time tracking    | ✓ | ✓ | ✓ | Table stakes
  Multi-warehouse       | ✓ | ✓ | - | Should have
  AI forecasting        | - | ✓ | - | Differentiator?
  Supplier management   | ✓ | ✓ | - | Should have
  Mobile app            | ✓ | ✓ | - | Should have

Derived Requirements (10):
  REQ-RES-001: System shall provide real-time inventory visibility [MUST]
  REQ-RES-002: System shall support multiple warehouse locations [SHOULD]
  REQ-RES-003: System shall integrate with barcode scanners [SHOULD]
  ... (7 more)

Confidence: LOW (based on public information)

Saved to: .requirements/inventory/research/RES-20251225-173000.yaml

Technical Research

/requirements-elicitation:research "React state management" --focus technical

Output:

Researching: React state management
Depth: moderate
Focus: technical

Querying MCP servers...
  [context7] resolving react library
  [context7] getting docs: state management
  [perplexity] React state management patterns 2025

Key Findings:

1. BUILT-IN OPTIONS
   - useState for local state
   - useReducer for complex state
   - Context API for global state (with caveats)

2. EXTERNAL LIBRARIES
   - Redux Toolkit (complex apps)
   - Zustand (simple, performant)
   - Jotai (atomic state)
   - React Query (server state)

3. RECOMMENDATIONS
   - Start simple (useState, Context)
   - Add complexity only when needed
   - Separate server state from client state

Technical Constraints:
  - React 18+ required for new patterns
  - SSR considerations for Next.js
  - Bundle size implications

Derived Requirements (5):
  REQ-RES-001: System shall use React 18 or later [CONSTRAINT]
  REQ-RES-002: System shall separate server state from client state [SHOULD]
  REQ-RES-003: System shall minimize bundle size impact of state library [SHOULD]
  ... (2 more)

Confidence: MEDIUM (verify with team)

Saved to: .requirements/frontend/research/RES-20251225-174500.yaml

Output Format

Saved YAML Structure

research_session:
  id: "RES-{timestamp}"
  topic: "{topic}"
  domain: "{domain}"
  depth: shallow|moderate|deep
  focus: "{focus area}"
  timestamp: "{ISO-8601}"

  queries:
    - server: perplexity
      query: "{query text}"
      success: true

    - server: context7
      library: "{library}"
      topic: "{topic}"
      success: true

  findings:
    category_1:
      - "{finding 1}"
      - "{finding 2}"

    category_2:
      - "{finding 3}"

  derived_requirements:
    - id: REQ-RES-001
      text: "{requirement}"
      source: research
      source_detail: "{specific source}"
      confidence: high|medium|low
      needs_validation: true
      priority: must|should|could

  recommendations:
    - "{recommendation 1}"
    - "{recommendation 2}"

  gaps_for_further_research:
    - "{topic needing more research}"

Integration

Follow-Up Commands

# Validate research with stakeholders
/requirements-elicitation:interview "Technical Lead" --context "validate React findings"

# Check if research fills gaps
/requirements-elicitation:gaps

# More research on specific topic
/requirements-elicitation:research "Zustand vs Redux" --focus technical --depth deep

# Consolidate all sources
/requirements-elicitation:discover "{domain}"

Agent Skills: Research Command

Install this agent skill to your local

Skill Files