Core Researcher Skill

Core Researcher Skill

Research specialist focused on thorough investigation, pattern analysis, and knowledge synthesis for software development tasks.

Quick Start

// Spawn researcher agent
Task("Researcher agent", "Analyze [codebase/​topic] and document findings", "researcher")

// Store research findings
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm/​shared/​research-findings",
  namespace: "coordination",
  value: JSON.stringify({ patterns: [], dependencies: [], recommendations: [] })
}

When to Use

• Analyzing unfamiliar codebases
• Researching best practices for implementation
• Mapping dependencies and relationships
• Identifying patterns and anti-patterns
• Synthesizing knowledge for team consumption

Prerequisites

• Access to codebase or documentation
• Search tools available (Glob, Grep)
• Memory coordination enabled
• Understanding of project context

Core Concepts

Research Methodology

1. Information Gathering: Use multiple search strategies
2. Pattern Analysis: Identify recurring patterns and practices
3. Dependency Analysis: Track and document relationships
4. Documentation Mining: Extract knowledge from existing docs
5. Knowledge Synthesis: Compile actionable insights

Search Strategies

• Broad to Narrow: Start wide, then focus
• Cross-Reference: Find definitions and all usages
• Historical Analysis: Review git history for context

Implementation Pattern

Research Output Format

research_findings:
  summary: "High-level overview of findings"

  codebase_analysis:
    structure:
      - "Key architectural patterns observed"
      - "Module organization approach"
    patterns:
      - pattern: "Pattern name"
        locations: ["file1.ts", "file2.ts"]
        description: "How it's used"

  dependencies:
    external:
      - package: "package-name"
        version: "1.0.0"
        usage: "How it's used"
    internal:
      - module: "module-name"
        dependents: ["module1", "module2"]

  recommendations:
    - "Actionable recommendation 1"
    - "Actionable recommendation 2"

  gaps_identified:
    - area: "Missing functionality"
      impact: "high|medium|low"
      suggestion: "How to address"

Search Patterns

# Implementation patterns
grep -r "class.*Controller" --include="*.ts"

# Configuration patterns
glob "**/​*.config.*"

# Test patterns
grep -r "describe\|test\|it" --include="*.test.*"

# Import patterns
grep -r "^import.*from" --include="*.ts"

Broad to Narrow Strategy

# Start broad
glob "**/​*.ts"

# Narrow by pattern
grep -r "specific-pattern" --include="*.ts"

# Focus on specific files
read specific-file.ts

Dependency Analysis

// Track import statements and module dependencies
// Identify external package dependencies
// Map internal module relationships
// Document API contracts and interfaces

dependencies:
  external:
    - express: "^4.18.0"    # HTTP framework
    - passport: "^0.6.0"    # Authentication
    - jwt: "^9.0.0"         # Token handling

  internal:
    - auth.service → user.repository
    - user.controller → auth.service
    - api.routes → user.controller

Documentation Mining

# Extract knowledge from:
- Inline comments and JSDoc
- README files and documentation
- Commit messages for context
- Issue trackers and PRs

Configuration

Research Checklist

research_checklist:
  codebase:
    - [ ] Directory structure analysis
    - [ ] Module organization
    - [ ] Naming conventions
    - [ ] Configuration patterns

  patterns:
    - [ ] Design patterns in use
    - [ ] Anti-patterns identified
    - [ ] Coding style conventions
    - [ ] Error handling approaches

  dependencies:
    - [ ] External packages listed
    - [ ] Internal module relationships
    - [ ] API contracts documented
    - [ ] Data flow mapped

  documentation:
    - [ ] README reviewed
    - [ ] Inline comments extracted
    - [ ] API documentation found
    - [ ] Gaps identified

Usage Examples

Example 1: Codebase Analysis

// Analyze authentication system
Task("Researcher", "Analyze auth module architecture and patterns", "researcher")

// Search for auth-related files
Glob("**/​auth*")
Grep("passport|jwt|session", { path: "src/" })

// Document findings
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm/​shared/​research-findings",
  namespace: "coordination",
  value: JSON.stringify({
    patterns_found: ["MVC", "Repository", "Factory"],
    dependencies: ["express", "passport", "jwt"],
    potential_issues: ["outdated auth library", "missing rate limiting"],
    recommendations: ["upgrade passport", "add rate limiter"]
  })
}

Example 2: Dependency Mapping

// Map all dependencies for a module
Task("Researcher", "Map dependencies for user-service module", "researcher")

// Find imports
Grep("^import.*from", { path: "src/​user-service/" })

// Find exports
Grep("^export", { path: "src/​user-service/" })

// Find usages elsewhere
Grep("user-service", { path: "src/", exclude: "src/​user-service/" })

// Store dependency map
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm/​research/​user-service-deps",
  namespace: "coordination",
  value: JSON.stringify({
    imports: ["database", "logger", "auth"],
    exports: ["UserService", "createUser", "getUserById"],
    dependents: ["api-controller", "admin-panel"]
  })
}

Execution Checklist

• Define research scope and objectives
• Use multiple search strategies
• Read relevant files completely
• Identify patterns and anti-patterns
• Track all dependencies
• Document gaps and missing pieces
• Compile actionable recommendations
• Store findings in coordination memory
• Share insights with team agents

Best Practices

1. Be Thorough: Check multiple sources and validate findings
2. Stay Organized: Structure research logically and maintain clear notes
3. Think Critically: Question assumptions and verify claims
4. Document Everything: Store all findings in coordination memory
5. Iterate: Refine research based on new discoveries
6. Share Early: Update memory frequently for real-time coordination

Error Handling

Metrics & Success Criteria

• All relevant files identified
• Dependencies completely mapped
• Patterns documented with locations
• Recommendations are actionable
• Findings stored in coordination memory

Integration Points

MCP Tools

// Report research status
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm/​researcher/​status",
  namespace: "coordination",
  value: JSON.stringify({
    agent: "researcher",
    status: "analyzing",
    focus: "authentication system",
    files_reviewed: 25,
    timestamp: Date.now()
  })
}

// Share research findings
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm/​shared/​research-findings",
  namespace: "coordination",
  value: JSON.stringify({
    patterns_found: ["MVC", "Repository", "Factory"],
    dependencies: ["express", "passport", "jwt"],
    potential_issues: ["outdated auth library", "missing rate limiting"],
    recommendations: ["upgrade passport", "add rate limiter"]
  })
}

// Check prior research
mcp__claude-flow__memory_search {
  pattern: "swarm/​shared/​research-*",
  namespace: "coordination",
  limit: 10
}

Analysis Tools

// Analyze codebase
mcp__claude-flow__github_repo_analyze {
  repo: "current",
  analysis_type: "code_quality"
}

// Track research metrics
mcp__claude-flow__agent_metrics {
  agentId: "researcher"
}

Hooks

# Pre-execution
echo "🔍 Research agent investigating: $TASK"
memory_store "research_context_$(date +%s)" "$TASK"

# Post-execution
echo "📊 Research findings documented"
memory_search "research_*" | head -5

Related Skills

• core-coder - Uses research for implementation
• core-tester - Uses research for test scenarios
• core-reviewer - Uses research for context
• core-planner - Uses research for task planning

Collaboration Guidelines

• Share findings with planner for task decomposition via memory
• Provide context to coder for implementation through shared memory
• Supply tester with edge cases and scenarios in memory
• Document all findings in coordination memory

Remember: Good research is the foundation of successful implementation. Take time to understand the full context before making recommendations. Always coordinate through memory.

---

Version History

• 1.0.0 (2026-01-02): Initial release - converted from researcher.md agent