andersonamaral2/claude-code-to-deep-agents-skills-converter/deep-agents-output

Name: deep-agents-output
Author: andersonamaral2

Claude Code and agent skill by andersonamaral2/claude-code-to-deep-agents-skills-converter

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community

By andersonamaral2
Coding
andersonamaral2/claude-code-to-deep-agents-skills-converter
examples/deep-agents-output/SKILL.md
Updated 23 Sep 2026
Version 1.0.01 version recorded

Source check pending

Checking that the SKILL.md file is still in the repository.

Creates a simple Todo API with FastAPI, SQLite, and basic CRUD operations.

Install

npx vskill@latest install andersonamaral2/claude-code-to-deep-agents-skills-converter/deep-agents-output

SKILL.md

Python FastAPI Todo App

Creates a simple Todo API with FastAPI, SQLite, and basic CRUD operations.

Execution Context

This skill runs inside Deep Agents CLI (v0.0.34+). Available tools:

Tool	Usage in this skill
`write_file`	Create project files (database.py, models.py, main.py, .env, .gitignore)
`execute`	Run shell commands (install deps, start server, run tests)
`read_file`	Read created files to verify content
`write_todos`	Track execution plan progress
`http_request`	Test API endpoints after server starts

Critical execution rules:

Always start by creating the plan via write_todos.
Create files one by one via write_file — never try to generate everything at once.
Test each module via execute immediately after creating it.
Use task to delegate long or parallel subtasks to sub-agents.

Execution Plan (use with `write_todos`)

When receiving the request, run write_todos with:

[ ] 1. Verify Python 3.11+ is installed
[ ] 2. Create project directory and virtual environment
[ ] 3. Install dependencies (fastapi, uvicorn, sqlalchemy)
[ ] 4. Create database module (app/database.py)
[ ] 5. Create models module (app/models.py)
[ ] 6. Create FastAPI application (app/main.py)
[ ] 7. Create .env and .gitignore files
[ ] 8. Start server and test all CRUD endpoints
[ ] 9. Run smoke tests for all endpoints

When to Use

Use this skill when the user asks to:

Create a todo app
Build a task manager API
Create a simple REST API with Python and FastAPI

Prerequisites Check

Before creating any files, use execute to verify:

bash

# Check Python version
python3 --version || { echo "ERROR: Python 3 not found"; exit 1; }
 
# Verify Python 3.11+
PYTHON_VERSION=$(python3 -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')")
echo "Python version: $PYTHON_VERSION"
 
# Check pip is available
python3 -m pip --version || { echo "ERROR: pip not found"; exit 1; }

If Python is not installed, use execute to install:

bash

# On macOS:
brew install python@3.11
 
# On Linux:
sudo apt-get update && sudo apt-get install -y python3.11 python3.11-venv

Steps

1. Setup Environment

Use execute to create the project directory and virtual environment:

bash

mkdir -p todo-api/app
cd todo-api
python3 -m venv venv
source venv/bin/activate

Use execute to install dependencies:

bash

cd todo-api && source venv/bin/activate
pip install fastapi uvicorn sqlalchemy

Test via execute:

bash

cd todo-api && source venv/bin/activate
python3 -c "import fastapi; import uvicorn; import sqlalchemy; print('All dependencies OK')"

2. Create Database Module

Use write_file to create todo-api/app/__init__.py:

python

Use write_file to create todo-api/app/database.py:

python

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
DATABASE_URL = "sqlite:///./todos.db"
engine = create_engine(DATABASE_URL, connect_args={"check_same_thread": False})
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base = declarative_base()

Test via execute:

bash

cd todo-api && source venv/bin/activate
python3 -c "from app.database import engine, SessionLocal, Base; print('database module OK')"

3. Create Models

Use write_file to create todo-api/app/models.py:

python

from sqlalchemy import Column, Integer, String, Boolean
from .database import Base
class Todo(Base):
    __tablename__ = "todos"
    id = Column(Integer, primary_key=True, index=True)
    title = Column(String, index=True)
    description = Column(String, default="")
    completed = Column(Boolean, default=False)

Test via execute:

bash

cd todo-api && source venv/bin/activate
python3 -c "from app.models import Todo; print(f'Model OK: {Todo.__tablename__}')"

4. Create FastAPI Application

Use write_file to create todo-api/app/main.py:

python

import os
from fastapi import FastAPI, HTTPException, Depends
from sqlalchemy.orm import Session
from typing import List
from pydantic import BaseModel
from .database import SessionLocal, engine
from .models import Todo as TodoModel, Base
Base.metadata.create_all(bind=engine)
app = FastAPI()
# Dependency
def get_db():
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()
class TodoCreate(BaseModel):
    title: str
    description: str = ""
    completed: bool = False
class TodoUpdate(BaseModel):
    title: str = None
    description: str = None
    completed: bool = None
class TodoResponse(BaseModel):
    id: int
    title: str
    description: str
    completed: bool
    class Config:
        from_attributes = True
@app.get("/todos", response_model=List[TodoResponse])
def list_todos(db: Session = Depends(get_db)):
    return db.query(TodoModel).all()
@app.post("/todos", response_model=TodoResponse)
def create_todo(todo: TodoCreate, db: Session = Depends(get_db)):
    db_todo = TodoModel(**todo.model_dump())
    db.add(db_todo)
    db.commit()
    db.refresh(db_todo)
    return db_todo
@app.put("/todos/{todo_id}", response_model=TodoResponse)
def update_todo(todo_id: int, todo: TodoUpdate, db: Session = Depends(get_db)):
    db_todo = db.query(TodoModel).filter(TodoModel.id == todo_id).first()
    if not db_todo:
        raise HTTPException(status_code=404, detail="Todo not found")
    
    update_data = todo.model_dump(exclude_unset=True)
    for key, value in update_data.items():
        setattr(db_todo, key, value)
    
    db.commit()
    db.refresh(db_todo)
    return db_todo
@app.delete("/todos/{todo_id}")
def delete_todo(todo_id: int, db: Session = Depends(get_db)):
    db_todo = db.query(TodoModel).filter(TodoModel.id == todo_id).first()
    if not db_todo:
        raise HTTPException(status_code=404, detail="Todo not found")
    
    db.delete(db_todo)
    db.commit()
    return {"message": "Todo deleted successfully"}
if __name__ == "__main__":
    import uvicorn
    host = os.getenv("API_HOST", "0.0.0.0")
    port = int(os.getenv("API_PORT", 8000))
    uvicorn.run(app, host=host, port=port)

Test via execute:

bash

cd todo-api && source venv/bin/activate
python3 -c "from app.main import app; print(f'FastAPI app OK: {len(app.routes)} routes')"

5. Environment Setup

Before execution, verify required environment variables via execute:

bash

# Check optional variables (with defaults)
echo "API_HOST=${API_HOST:-0.0.0.0} (default: 0.0.0.0)"
echo "API_PORT=${API_PORT:-8000} (default: 8000)"

Use write_file to create todo-api/.env:

API_HOST=0.0.0.0
API_PORT=8000

Use write_file to create todo-api/.gitignore:

venv/
__pycache__/
*.pyc
*.db
.env

6. Add Project Notes

Use write_file to create todo-api/AGENTS.md:

markdown

# Todo API — Project Notes
 
-Framework: FastAPI with SQLAlchemy ORM
-Database: SQLite (file: todos.db)
-No authentication required
-Environment: API_HOST, API_PORT configurable via .env
-Endpoints: GET/POST /todos, PUT/DELETE /todos/{id}

7. Test the API

Use execute to start the server in the background:

bash

cd todo-api && source venv/bin/activate
nohup python3 -m app.main > server.log 2>&1 &
echo $! > server.pid
sleep 2
echo "Server PID: $(cat server.pid)"

Use execute to run smoke tests on all endpoints:

bash

echo "=== Testing GET /todos ==="
curl -s -o /dev/null -w "%{http_code}" http://localhost:8000/todos
echo ""
 
echo "=== Testing POST /todos ==="
curl -s -o /dev/null -w "%{http_code}" -X POST http://localhost:8000/todos \
  -H "Content-Type: application/json" \
  -d '{"title": "Buy milk", "completed": false}'
echo ""
 
echo "=== Testing PUT /todos/1 ==="
curl -s -o /dev/null -w "%{http_code}" -X PUT http://localhost:8000/todos/1 \
  -H "Content-Type: application/json" \
  -d '{"completed": true}'
echo ""
 
echo "=== Testing DELETE /todos/1 ==="
curl -s -o /dev/null -w "%{http_code}" -X DELETE http://localhost:8000/todos/1
echo ""
 
echo "=== All smoke tests complete ==="

Use execute to stop the test server:

bash

cd todo-api && kill $(cat server.pid) 2>/dev/null; rm -f server.pid

Notes

Keep it simple, no authentication required
Uses SQLite to avoid external database dependencies
Follows FastAPI best practices with Pydantic models
Supports configuration via environment variables

Usage with Deep Agents CLI

Mode 1 — Build (one-shot)

bash

deepagents -y "Create a Python FastAPI Todo App following the python-fastapi-todo-app skill"

Mode 2 — Interactive

bash

deepagents
> Create a todo API with FastAPI and SQLite

Mode 3 — Non-interactive (CI/CD)

bash

deepagents -n -y -S "pip,python3,curl,mkdir" "Create a FastAPI todo app with CRUD endpoints"

Troubleshooting

Python not found

bash

# Check:
python3 --version
# Install (macOS):
brew install python@3.11
# Install (Linux):
sudo apt-get install python3.11

pip install fails

bash

# Ensure venv is activated:
source venv/bin/activate
# Upgrade pip:
python3 -m pip install --upgrade pip
# Retry:
pip install fastapi uvicorn sqlalchemy

Environment variable not set

bash

# Check what's set:
env | grep API_
# Set manually:
export API_HOST="0.0.0.0"
export API_PORT=8000
# Or load from .env:
set -a && source .env && set +a

Server won't start

bash

# Check if port is in use:
lsof -i :8000
# Check server logs:
cat server.log
# Try a different port:
export API_PORT=8001

Context window overflow

Use /compact to force compaction before continuing.
Consider splitting the task with `task` sub-agents.

Security

Security scanPassed, 95 of 100Pattern checks on the skill's files.
Model reviewPassed

See the full security report

Quality evaluation

Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

See evaluation results

Source

SKILL.md in the repositoryCheckingexamples/deep-agents-output/SKILL.md

Popularity

Repository stars: 55
Repository forks: 8
7-day trend score: 20

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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Install

SKILL.md

Python FastAPI Todo App

Execution Context

Execution Plan (use with write_todos)

When to Use

Prerequisites Check

Steps

1. Setup Environment

2. Create Database Module

3. Create Models

4. Create FastAPI Application

5. Environment Setup

6. Add Project Notes

7. Test the API

Notes

Usage with Deep Agents CLI

Mode 1 — Build (one-shot)

Mode 2 — Interactive

Mode 3 — Non-interactive (CI/CD)

Troubleshooting

Python not found

pip install fails

Environment variable not set

Server won't start

Context window overflow

Security

Quality evaluation

Source

Popularity

Works with

Execution Plan (use with `write_todos`)