| name | dev-server |
| description | Create and manage Python backend services using uv, FastAPI, Pydantic, SQLAlchemy, and AI libraries. Use this skill when the user asks to build a backend, API, or server-side application. |
| metadata | {"author":"Yuga Sun","version":"2026.01.29"} |
Server Development Skill
Instructions
Use this skill to scaffold and maintain backend services in the server/ directory. Follow the stack preferences and configuration details below.
Quick Start
- Initialize:
uv init.
- Manager: Use
uv for all dependency operations.
- Framework: Setup
FastAPI with Pydantic.
- Database: configure
SQLAlchemy (Async) + Alembic.
Core Stack Preferences
Project Management (uv)
Use uv for all Python project management (scaffolding, dependency management, virtual environments).
| Command | Description |
|---|
uv init | Initialize a new project |
uv add <pkg> | Add dependency |
uv add --dev <pkg> | Add development dependency |
uv run <cmd> | Run command in virtual environment |
uv venv | Create virtual environment |
Project Location
The backend project should be initialized in the server/ directory.
Framework (FastAPI)
Use FastAPI for building APIs.
- Use
APIRouter for modularizing routes.
- Use
pydantic-settings for configuration management.
Database (SQLAlchemy + Alembic)
Use SQLAlchemy 2.0+ with AsyncIO support.
Use Alembic for database migrations.
AI & LLM (LiteLLM + Docling)
- LiteLLM: For standardized access to various LLM providers.
- Docling: For parsing and processing documents.
References
Setup & Configuration
| Topic | Description | Reference |
|---|
| Project Setup | Using uv, strict python versioning, and environment variables | setup |
| API Development | FastAPI structure, error handling, and validation | api |
Data & Architecture
| Topic | Description | Reference |
|---|
| Database Access | Async SQLAlchemy strategies and Alembic migrations | database |
| AI Integration | using LiteLLM and Docling for AI features | ai |