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Found 15 Skills
Alembic migration patterns for SQLAlchemy 2.0 async. Use when creating database migrations, managing schema versions, handling zero-downtime deployments, or implementing reversible database changes.
FastAPI with PostgreSQL, async SQLAlchemy 2.0, Alembic, and Docker.
Expert guidance for SQLAlchemy 2.0 + Pydantic + PostgreSQL. Use when setting up database layers, defining models, creating migrations, or any database-related work. Automatically activated for DB tasks.
SQLAlchemy ORM and Alembic migration best practices for building safe, performant database schemas. This skill should be used when writing, reviewing, or refactoring SQLAlchemy models, Alembic migrations, or database query patterns. Triggers on tasks involving SQLAlchemy ORM, Alembic migrations, database schema changes, or query optimization.
Reviews SQLAlchemy code for session management, relationships, N+1 queries, and migration patterns. Use when reviewing SQLAlchemy 2.0 code, checking session lifecycle, relationship() usage, or Alembic migrations.
Advanced SQLModel patterns and comprehensive database migrations with Alembic. Use when creating SQLModel models, defining relationships (one-to-many, many-to-many, self-referential), setting up database migrations, optimizing queries, solving N+1 problems, implementing inheritance patterns, working with composite keys, creating indexes, performing data migrations, or troubleshooting Alembic issues. Triggers include "SQLModel", "Alembic migration", "database model", "relationship", "foreign key", "migration", "N+1 query", "query optimization", "database schema", or questions about ORM patterns.
PostgreSQL best practices: multi-tenancy with RLS, schema design, Alembic migrations, async SQLAlchemy, and query optimization.
SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work.
Comprehensive Alembic database migration management for customer support systems
Python backend implementation patterns for FastAPI applications with SQLAlchemy 2.0, Pydantic v2, and async patterns. Use during the implementation phase when creating or modifying FastAPI endpoints, Pydantic models, SQLAlchemy models, service layers, or repository classes. Covers async session management, dependency injection via Depends(), layered error handling, and Alembic migrations. Does NOT cover testing (use pytest-patterns), deployment (use deployment-pipeline), or FastAPI framework mechanics like middleware and WebSockets (use fastapi-patterns).
Generate Python FastAPI code following project design patterns. Use when creating models, schemas, repositories, services, controllers, database migrations, authentication, or tests. Enforces layered architecture, async patterns, OWASP security, and Alembic migration naming conventions (yyyymmdd_HHmm_feature).
Guides the agent through async database integration with SQLAlchemy and Alembic migrations for FastAPI applications. Triggered when users ask to "set up a database", "create database models", "add SQLAlchemy", "create migrations", "run Alembic", "connect to PostgreSQL", "add a database layer", "create CRUD operations", "set up async database", or mention SQLAlchemy, Alembic, ORM, database models, async database, connection pool, or database migrations.