/research
Research technical topics and best practices using AI-powered analysis.
Overview
The /research prompt helps you quickly gather information about technical topics, compare approaches, and discover best practices. It uses the Gemini AI model to provide comprehensive research results with actionable recommendations.
When to Use
Use /research when you need to:
- Understand new technologies or frameworks
- Compare different approaches (e.g., "GraphQL vs REST")
- Discover best practices for specific scenarios
- Research implementation patterns
- Explore security considerations
- Find modern solutions to technical challenges
Syntax
/research <topic>Arguments
- topic (required): The technical topic or question to research
Examples
Basic Research
/research authentication best practices
/research React Server Components
/research WebSocket implementationComparative Research
/research GraphQL vs REST for SaaS
/research PostgreSQL vs MongoDB for real-time apps
/research Monolith vs MicroservicesSpecific Scenarios
/research multi-tenant database architecture
/research handling file uploads in Next.js
/research implementing real-time featuresWhat It Does
- Analyzes the Topic: Understands your research query and context
- Gathers Information: Uses AI to compile relevant information
- Structures Findings: Organizes results into categories:
- Best practices
- Implementation patterns
- Tools and libraries
- Common approaches
- Anti-patterns to avoid
- Provides Recommendations: Offers specific advice for your project
- Includes Examples: Shows code snippets and implementation details
- Lists Resources: Provides documentation links and references
Output Structure
The research results include:
Executive Summary
A brief overview of key findings and recommendations
Detailed Findings
Categorized insights:
- Best Practices: Proven approaches
- Patterns: Common implementation patterns
- Tools: Relevant libraries and frameworks
- Approaches: Different ways to solve the problem
Recommendations
Specific advice based on your project context with priority levels:
- Must-have recommendations
- Should-have suggestions
- Nice-to-have options
Code Examples
Practical implementation snippets showing how to apply the research
Trade-offs
Analysis of different approaches with pros and cons
Resources
Links to documentation, tutorials, and further reading
Memory Recommendations
Suggestions for what to document in your project's CLAUDE.md files
Integration with Other Prompts
Research results can inform other prompts:
- Use findings with
/execute-taskto implement recommendations - Apply patterns with
/generate-implementation-tutorial - Document insights with
/document-feature - Extract patterns with
/extract-patterns
Best Practices
- Be Specific: More detailed queries yield better results
- Include Context: Mention your tech stack or constraints
- Ask Comparisons: Great for evaluating options
- Follow Up: Use research to guide implementation
Technical Details
- Tool Used:
research- AI-powered research tool - AI Model: Gemini (optimized for technical research)
- Fallback: Provides basic guidance if AI is unavailable
Common Use Cases
Technology Selection
/research best frontend framework for SaaS in 2024
/research choosing between Supabase and FirebaseArchitecture Decisions
/research event-driven architecture patterns
/research implementing CQRS with Event SourcingSecurity Research
/research JWT vs session authentication
/research implementing zero-trust securityPerformance Optimization
/research database query optimization techniques
/research caching strategies for web applicationsLimitations
- Results are based on AI knowledge cutoff
- Always verify critical security recommendations
- Consider your specific context when applying advice
- Some cutting-edge topics may have limited information
Related Commands
/discover-context- Analyze existing code patterns/extract-patterns- Extract patterns from your codebase/document-feature- Document your implementations/orchestrate- Plan features based on research
