agusmdev

Codebase health scanner and technical debt tracker. Use when the user asks about code quality, technical debt, dead code, large files, god classes, duplicate functions, code smells, naming issues, import cycles, or coupling problems. Also use when asked for a…

Configure Alembic for async SQLAlchemy migrations with PostgreSQL

Create FastAPI application factory with lifespan, middleware, pagination, and router configuration

Implement session-based authentication in FastAPI applications. Use when building login/logout flows, protecting endpoints with auth dependencies, creating user models with password hashing, managing sessions in database, or implementing auth exceptions.…

Overview and guidelines for FastAPI 3-layer architecture with async SQLAlchemy, Pydantic v2, and best practices

Create SQLAlchemy base model with UUID, timestamp, and soft delete mixins for FastAPI

Create abstract base repository interface with CRUD, pagination, filtering, bulk operations, and soft delete

Create Pydantic v2 base schemas for request validation and response serialization in FastAPI

OpenProse is a programming language for AI sessions. An AI session is a Turing-complete computer; OpenProse structures English into unambiguous control flow. More pattern than framework—it ships as a skill with no dependencies. Activate when: running .prose…

Configure Alembic for async SQLAlchemy migrations with PostgreSQL

Create FastAPI application factory with lifespan, middleware, pagination, and router configuration

Overview and guidelines for FastAPI 3-layer architecture with async SQLAlchemy, Pydantic v2, and best practices

Create SQLAlchemy base model with UUID, timestamp, and soft delete mixins for FastAPI

Create abstract base repository interface with CRUD, pagination, filtering, bulk operations, and soft delete

Create Pydantic v2 base schemas for request validation and response serialization in FastAPI

Create base service class that wraps repository operations and provides business logic hooks

Run an iterative, measured optimization loop — try an idea, benchmark it, keep what improves the metric, revert what doesn't, repeat — leaving an auditable trail of commits. Use this when the user wants to ITERATIVELY optimize a measurable target and expects…

Optimize smart-linter linting speed without breaking rule detection or tests