Triggering Memory Storage & Retrieval

User Request → Agent Starts Task → Performs Work → Task Completion → Memory Storage

New User Request → Context Analysis → Memory Search → Relevant Knowledge → Enhanced Response

Vibe Coding Agent ←→ MCP Server ←→ ByteRover Memory System
      ↑                    ↑                    ↑
Custom Rules      Tool Exposure       Knowledge Storage

// Example requests for manual storage
"Store this API integration pattern for future reference"
"Remember this debugging approach for React performance issues" 
"Save this deployment configuration as a reusable template"

// Example requests for manual retrieval  
"What did we learn about handling authentication in microservices?"
"Retrieve our previous approaches to database migration strategies"
"Show me the error handling patterns we've used for API calls"

Rule: "Always store knowledge after debugging production issues"
Trigger: Error resolution in production environment
Action: Capture debugging steps, root cause, and solution

Rule: "Check memory before implementing new features"
Trigger: Feature development requests
Action: Search for similar implementations and patterns

Store knowledge ONLY when:
- Solution required significant research
- Novel approach was discovered  
- Error took > 30 minutes to resolve
- Architecture decision was made

Retrieve knowledge based on:
- Current technology stack
- Problem domain similarity
- Team member involvement
- Project complexity level

✅ Good Balance:
- Let automation handle routine storage/retrieval
- Manually control critical knowledge capture
- Use custom rules for team-specific workflows
- Override defaults for complex projects

❌ Over-Control:
- Manually managing every memory operation
- Complex rules for simple tasks
- Disabling automatic behavior entirely
- Micro-managing knowledge storage

// In your agent interaction
"Before we start this feature, check what we learned about similar implementations"
// Agent uses retrieve-knowledge

"After implementing the authentication system, save the key decisions and patterns"
// Agent uses store-knowledge

When working on payment processing features:
"Before implementing any payment logic, retrieve our previous approaches to PCI compliance, fraud detection patterns, and secure transaction handling. After completion, store the payment flow decisions, security measures implemented, and any regulatory compliance insights."

When handling financial calculations:
"Search our memory for precision handling in financial calculations, currency conversion patterns, and rounding strategies. After implementing the feature, save the mathematical approaches used and any edge cases discovered."

When building audit systems:
"Retrieve knowledge about financial audit trails, logging requirements, and compliance reporting patterns. Store the audit implementation details and regulatory compliance notes after completion."

When developing checkout systems:
"Check our memory for cart persistence strategies, payment gateway integrations, and user experience patterns. After building the checkout flow, store the UX decisions, performance optimizations, and conversion insights."

When implementing inventory management:
"Retrieve our approaches to stock tracking, reservation systems, and inventory synchronization. Store the chosen algorithms, data consistency strategies, and scalability considerations."

When building patient data features:
"Before handling patient information, retrieve our HIPAA compliance patterns, data encryption approaches, and access control strategies. Store the privacy implementation details and compliance verification steps."

When developing medical workflow systems:
"Check memory for healthcare workflow automation, approval processes, and integration with medical systems. Save the workflow design decisions and regulatory compliance measures."