database-analyst

Usage

This skill analyzes database interactions, schema definitions, and migration scripts. It supports:

• Languages: Java (Spring Data JPA, Hibernate), Kotlin (Exposed), Python (SQLAlchemy, Alembic)
• Tasks: Performance analysis, Schema design review, Application logic audit, ERD generation.

Workflows

1. Identify Technology Stack

First, determine the database technology in use by checking configuration files:

• Java/Spring: Look for pom.xml (dependencies like spring-boot-starter-data-jpa, flyway-core), application.properties, and Entity classes (@Entity).
• Python: Look for requirements.txt (sqlalchemy, alembic), alembic.ini, and model definitions (Base = declarative_base()).

2. Select Analysis Mode

Based on the user's request, perform the following:

A. Performance & Migration Analysis

For requests about "slow queries", "locking", "migrations", or "tuning":

1. Locate migration files (e.g., src/main/resources/db/migration/*.sql or alembic/versions/*.py).
2. Review for locking risks and anti-patterns.
3. Read references/performance.md for specific checklists.

B. Schema Design & ERD

For requests about "normalization", "schema review", "database structure", or "diagrams":

1. Locate Entity/Model classes.
2. Analyze relationships, constraints, and keys.
3. Read references/schema.md for normalization rules and ERD formatting.

C. Application Logic & Query Analysis

For requests about "N+1 problems", "repository review", or "transaction issues":

1. Locate Repository/DAO layers and Service layers.
2. Trace method calls to identify implicit queries.
3. Read references/java-jpa.md for Java/Spring specifics.
4. Read references/python-sqlalchemy.md for Python specifics.

Output Format

• Analysis: Group findings by "Critical", "Warning", and "Info".
• ERD: Use Mermaid diagram format unless requested otherwise.
• Recommendations: Provide concrete code snippets for fixes (e.g., adding an index, refactoring a query).