What types of databases can this skill evaluate?

The Database Schema Evaluator supports a wide range of paradigms including relational (SQL), document (NoSQL), graph, and time-series databases.

What is included in the final evaluation report?

The report includes an executive summary, expert findings, a consolidated risk matrix, a detailed scoring matrix, and specific technical recommendations for implementation.

Does it identify specific normalization issues?

Yes, the Data Architect persona specifically checks for compliance with normalization forms (1NF-5NF, BCNF) and identifies problematic design anti-patterns.

Can it compare two different schema designs?

Yes, it features a comparison mode specifically designed to analyze the tradeoffs between different architectural approaches for the same business requirement.

How does the multi-perspective analysis work?

The skill simulates five distinct expert personas—Data Architect, Performance Engineer, Integrity Guardian, Evolution Strategist, and Operations Specialist—to provide a 360-degree evaluation.

Database Schema Evaluator

Name: Database Schema Evaluator
Author: Agentient

byAgentient

Database Management

Performs comprehensive multi-perspective audits of database architectures to optimize performance, integrity, and long-term scalability.

About

The Database Schema Evaluator is a specialized Claude Code skill that provides expert-level reviews of database designs through a simulated panel of technical specialists. By analyzing schemas through five distinct lenses—Data Architecture, Performance Engineering, Data Integrity, Evolution Strategy, and Operations—it identifies normalization errors, potential bottlenecks, and migration risks before they reach production. This tool is essential for developers and architects who need to validate complex data models, compare architectural tradeoffs, and ensure their data foundation is robust enough to handle future growth.

Key Features

Tradeoff analysis for comparing normalized versus denormalized approaches
Quantitative scoring across dimensions like Correctness, Scalability, and Robustness
Automated risk assessment with likelihood, impact, and mitigation strategies
Simulated expert panel analysis including Data Architects and Performance Engineers
Detailed reporting with immediate actionable fixes and long-term improvements
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Use Cases

Comparing multiple architectural approaches for microservices data migration
Reviewing new database schemas for normalization and integrity before deployment
Evaluating existing schemas for refactoring to solve performance bottlenecks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add agentient/vibekit database-schema-evaluator

For use in Claude.ai and ChatGPT

Download Skill

GitHub