mastra-system-check

🥈Silver

Claude Code skill that validates Mastra AI agent projects with 66 checks across configuration, agents, workflows, memory, tools, prompts, and security.

800Updated 2mo ago

Intermediate30min to implementautomation

Saves ~30 min per use

Quick InstallView Source

git clone https://github.com/goldk3y/mastra-system-check.git

Works with:

Claude

Overview

About This Skill

Claude Code skill that validates Mastra AI agent projects with 66 checks across configuration, agents, workflows, memory, tools, prompts, and security.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/goldk3y/mastra-system-check

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Validate my Mastra AI agent project with the 66-point system check. Here's the project details: [PROJECT_NAME], [INDUSTRY], [KEY_OBJECTIVES]. Please provide a detailed report with any issues found and recommendations for improvement.

Example Output

# 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.