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Found 42 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.
Robyn backend scaffolding and architecture guidance for projects using robyn-config. Use when creating or evolving Robyn services, choosing DDD vs MVC, choosing SQLAlchemy vs Tortoise, adding new entities/routes/repositories with robyn-config add, auditing Robyn backend quality, or authoring and improving skill markdown for Robyn engineering workflows.
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.
Build production database layers with SQLAlchemy ORM and PostgreSQL. This skill should be used when teaching students to define data models, manage sessions, perform CRUD operations, and connect to PostgreSQL/Neon databases.
This skill should be used when the user asks to "set up Alembic migrations", "create a database migration", "run alembic upgrade", "configure alembic autogenerate", or needs guidance on SQLAlchemy schema versioning and migration best practices.
Debug Flask applications systematically with this comprehensive troubleshooting skill. Covers routing errors (404/405), Jinja2 template issues, application context problems, SQLAlchemy session management, blueprint registration failures, and circular import resolution. Provides structured four-phase debugging methodology with Flask-specific tools including Werkzeug debugger, Flask-DebugToolbar, and Flask shell for interactive investigation.
Python backend patterns for asyncio, FastAPI, SQLAlchemy 2.0 async, and connection pooling. Use when building async Python services, FastAPI endpoints, database sessions, or connection pool tuning.
Galaxy database migration with Alembic - create schema changes (add table/column), upgrade/downgrade database versions, check migration status, troubleshoot errors. Use for: SQLAlchemy model changes, database schema modifications, Alembic revisions, migration version conflicts, lib/galaxy/model changes.
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke for async SQLAlchemy, JWT authentication, WebSockets, OpenAPI documentation.
FastAPI with PostgreSQL, async SQLAlchemy 2.0, Alembic, and Docker.
Structured observability with Pydantic Logfire and OpenTelemetry. Use when: (1) Adding traces/logs to Python APIs, (2) Instrumenting FastAPI, HTTPX, SQLAlchemy, or LLMs, (3) Setting up service metadata, (4) Configuring sampling or scrubbing sensitive data, (5) Testing observability code.
Expert guidance for building production-ready FastAPI applications with modular architecture where each business domain is an independent module with own routes, models, schemas, services, cache, and migrations. Uses UV + pyproject.toml for modern Python dependency management, project name subdirectory for clean workspace organization, structlog (JSON+colored logging), pydantic-settings configuration, auto-discovery module loader, async SQLAlchemy with PostgreSQL, per-module Alembic migrations, Redis/memory cache with module-specific namespaces, central httpx client, OpenTelemetry/Prometheus observability, conversation ID tracking (X-Conversation-ID header+cookie), conditional Keycloak/app-based RBAC authentication, DDD/clean code principles, and automation scripts for rapid module development. Use when user requests FastAPI project setup, modular architecture, independent module development, microservice architecture, async database operations, caching strategies, logging patterns, configuration management, authentication systems, observability implementation, or enterprise Python web services. Supports max 3-4 route nesting depth, cache invalidation patterns, inter-module communication via service layer, and comprehensive error handling workflows.