mastra-system-check

# Mastra AI Agent Project Validation Report

## Project Overview
- **Project Name**: SmartRetail Assistant
- **Industry**: Retail
- **Key Objectives**: Improve customer service, streamline inventory management, and enhance sales analytics

## Validation Results
### Configuration
✅ All required configuration files are present
⚠️  `agent_config.yaml` has deprecated parameters (lines 12-15)

### Agents
✅ All agents have unique and descriptive names
⚠️  `inventory_agent` lacks a fallback mechanism for API failures

### Workflows
✅ Workflows are well-structured and follow best practices
⚠️  `order_processing_workflow` has a potential deadlock scenario in step 3

### Memory
✅ Memory settings are optimized for the project's scale
⚠️  `customer_service_agent` memory retention period is too short (currently 7 days, consider 30 days)

### Tools
✅ All tools are properly integrated and documented
⚠️  `inventory_management_tool` lacks error handling for rate limits

### Prompts
✅ Prompts are clear, concise, and context-aware
⚠️  `customer_support_prompt` could benefit from more specific examples

### Security
✅ Security measures are in place and up-to-date
⚠️  Consider implementing role-based access control for sensitive operations

## Recommendations
1. Update deprecated parameters in `agent_config.yaml`
2. Implement a fallback mechanism for `inventory_agent`
3. Review and resolve the deadlock scenario in `order_processing_workflow`
4. Extend memory retention period for `customer_service_agent`
5. Add error handling for rate limits in `inventory_management_tool`
6. Enhance `customer_support_prompt` with specific examples
7. Implement role-based access control for sensitive operations

## Overall Assessment
The project is well-structured and follows best practices in most areas. However, there are several areas that could be improved to enhance reliability, security, and user experience. Addressing the issues mentioned above will significantly improve the project's robustness and performance.