Claude-skill-registry core-researcher
Deep research and information gathering specialist for thorough investigation, pattern analysis, and knowledge synthesis
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/core-researcher" ~/.claude/skills/majiayu000-claude-skill-registry-core-researcher && rm -rf "$T"
manifest:
skills/data/core-researcher/SKILL.mdtags
source content
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
- Information Gathering: Use multiple search strategies
- Pattern Analysis: Identify recurring patterns and practices
- Dependency Analysis: Track and document relationships
- Documentation Mining: Extract knowledge from existing docs
- 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
- Be Thorough: Check multiple sources and validate findings
- Stay Organized: Structure research logically and maintain clear notes
- Think Critically: Question assumptions and verify claims
- Document Everything: Store all findings in coordination memory
- Iterate: Refine research based on new discoveries
- Share Early: Update memory frequently for real-time coordination
Error Handling
| Issue | Recovery |
|---|---|
| File not found | Check alternative paths/names |
| Pattern too broad | Add more specific filters |
| Missing context | Expand search scope |
| Conflicting info | Cross-reference multiple sources |
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