MR
Mayur Rathi
@mayurrathi
⭐ 40.7k GitHub stars

Python Development Python Scaffold

Python Development Python Scaffold is an code AI skill with a core value of You are a Python project architecture expert specializing in scaffolding production-ready Python applications. It helps developers solve real-world problems in the code domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

Last verified on: 2026-07-07

Quick Facts

Category code
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-07
Risk Level Low
mkdir -p ./skills/python-development-python-scaffold && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/python-development-python-scaffold/SKILL.md -o ./skills/python-development-python-scaffold/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Python Project Scaffolding


You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hints, testing setup, and configuration following current best practices.


Use this skill when


- Working on python project scaffolding tasks or workflows

- Needing guidance, best practices, or checklists for python project scaffolding


Do not use this skill when


- The task is unrelated to python project scaffolding

- You need a different domain or tool outside this scope


Context


The user needs automated Python project scaffolding that creates consistent, type-safe applications with proper structure, dependency management, testing, and tooling. Focus on modern Python patterns and scalable architecture.


Requirements


$ARGUMENTS


Instructions


1. Analyze Project Type


Determine the project type from user requirements:

- **FastAPI**: REST APIs, microservices, async applications

- **Django**: Full-stack web applications, admin panels, ORM-heavy projects

- **Library**: Reusable packages, utilities, tools

- **CLI**: Command-line tools, automation scripts

- **Generic**: Standard Python applications


2. Initialize Project with uv


bash
# Create new project with uv
uv init <project-name>
cd <project-name>

# Initialize git repository
git init
echo ".venv/" >> .gitignore
echo "*.pyc" >> .gitignore
echo "__pycache__/" >> .gitignore
echo ".pytest_cache/" >> .gitignore
echo ".ruff_cache/" >> .gitignore

# Create virtual environment
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Generate FastAPI Project Structure


text
fastapi-project/
├── pyproject.toml
├── README.md
├── .gitignore
├── .env.example
├── src/
│   └── project_name/
│       ├── __init__.py
│       ├── main.py
│       ├── config.py
│       ├── api/
│       │   ├── __init__.py
│       │   ├── deps.py
│       │   ├── v1/
│       │   │   ├── __init__.py
│       │   │   ├── endpoints/
│       │   │   │   ├── __init__.py
│       │   │   │   ├── users.py
│       │   │   │   └── health.py
│       │   │   └── router.py
│       ├── core/
│       │   ├── __init__.py
│       │   ├── security.py
│       │   └── database.py
│       ├── models/
│       │   ├── __init__.py
│       │   └── user.py
│       ├── schemas/
│       │   ├── __init__.py
│       │   └── user.py
│       └── services/
│           ├── __init__.py
│           └── user_service.py
└── tests/
    ├── __init__.py
    ├── conftest.py
    └── api/
        ├── __init__.py
        └── test_users.py

**pyproject.toml**:

toml
[project]
name = "project-name"
version = "0.1.0"
description = "FastAPI project description"
requires-python = ">=3.11"
dependencies = [
    "fastapi>=0.110.0",
    "uvicorn[standard]>=0.27.0",
    "pydantic>=2.6.0",
    "pydantic-settings>=2.1.0",
    "sqlalchemy>=2.0.0",
    "alembic>=1.13.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=8.0.0",
    "pytest-asyncio>=0.23.0",
    "httpx>=0.26.0",
    "ruff>=0.2.0",
]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]

[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"

**src/project_name/main.py**:

python
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from .api.v1.router import api_router
from .config import settings

app = FastAPI(
    title=settings.PROJECT_NAME,
    version=settings.VERSION,
    openapi_url=f"{settings.API_V1_PREFIX}/openapi.json",
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=settings.ALLOWED_ORIGINS,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app.include_router(api_router, prefix=settings.API_V1_PREFIX)

@app.get("/health")
async def health_check() -> dict[str, str]:
    return {"status": "healthy"}

4. Generate Django Project Structure


bash
# Insta

🎯 Best For

  • Developers scaffolding new projects
  • Prototype builders
  • Claude users
  • Software engineers
  • Development teams

💡 Use Cases

  • Bootstrapping React components
  • Creating API route handlers
  • Python code quality enforcement
  • Dependency management

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Python Development Python Scaffold to Your Work

    Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.

  4. 4

    Review and Refine

    Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.

❓ Frequently Asked Questions

Can I customize the generated output?

Yes — modify the skill's prompt instructions to match your project conventions and coding style.

Is Python Development Python Scaffold compatible with Cursor and VS Code?

Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.

Do I need specific dependencies for Python Development Python Scaffold?

Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.

How do I install Python Development Python Scaffold?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/python-development-python-scaffold/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Using generated code without understanding

Understand what generated code does before shipping it to production.

Skipping validation

Always test AI-generated code changes, even for simple refactors.

Missing dependency updates

Check if the skill requires updated dependencies or new packages.

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