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/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 implementation

Comparative Research

/research GraphQL vs REST for SaaS
/research PostgreSQL vs MongoDB for real-time apps
/research Monolith vs Microservices

Specific Scenarios

/research multi-tenant database architecture
/research handling file uploads in Next.js
/research implementing real-time features

What It Does

  1. Analyzes the Topic: Understands your research query and context
  2. Gathers Information: Uses AI to compile relevant information
  3. Structures Findings: Organizes results into categories:
    • Best practices
    • Implementation patterns
    • Tools and libraries
    • Common approaches
    • Anti-patterns to avoid
  4. Provides Recommendations: Offers specific advice for your project
  5. Includes Examples: Shows code snippets and implementation details
  6. 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-task to implement recommendations
  • Apply patterns with /generate-implementation-tutorial
  • Document insights with /document-feature
  • Extract patterns with /extract-patterns

Best Practices

  1. Be Specific: More detailed queries yield better results
  2. Include Context: Mention your tech stack or constraints
  3. Ask Comparisons: Great for evaluating options
  4. 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 Firebase

Architecture Decisions

/research event-driven architecture patterns
/research implementing CQRS with Event Sourcing

Security Research

/research JWT vs session authentication
/research implementing zero-trust security

Performance Optimization

/research database query optimization techniques
/research caching strategies for web applications

Limitations

  • 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
  • /discover-context - Analyze existing code patterns
  • /extract-patterns - Extract patterns from your codebase
  • /document-feature - Document your implementations
  • /orchestrate - Plan features based on research

Built with ❤️ for the AI Coding community, by Praney Behl