implementation

Feature Implementation Skill

Purpose

This skill provides systematic guidance for implementing features with high-quality code, comprehensive tests, and proper documentation, following project standards and best practices.

When to Use

• After design phase is complete and approved
• Need to implement code for a feature
• Writing unit and integration tests
• Creating technical documentation
• Following TDD (Test-Driven Development) workflow

Implementation Workflow

1. Setup and Preparation

Review Design Document:

• Read architecture design from previous phase
• Understand component structure
• Review API contracts and data models
• Note security and performance requirements

Setup Development Environment:

# Activate virtual environment
source venv/bin/activate  # or: uv venv && source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt
# or: uv pip install -r requirements.txt

# Install dev dependencies
pip install -e ".[dev]"

Create Feature Branch:

git checkout -b feature/feature-name

Deliverable: Development environment ready

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2. Test-Driven Development (TDD)

TDD Cycle: Red → Green → Refactor

Step 1: Write Failing Test (Red)

# tests/test_feature.py
import pytest
from feature import process_data

def test_process_data_success():
    """Test successful data processing."""
    # Arrange
    input_data = {"name": "test", "value": 123}

    # Act
    result = process_data(input_data)

    # Assert
    assert result.name == "test"
    assert result.value == 123

Step 2: Write Minimal Code (Green)

# src/tools/feature/core.py
def process_data(input_data: dict):
    """Process input data."""
    # Minimal implementation to pass test
    return type('Result', (), input_data)()

Step 3: Refactor (Refactor)

# src/tools/feature/core.py
from .models import InputModel, ResultModel

def process_data(input_data: dict) -> ResultModel:
    """
    Process input data and return result.

    Args:
        input_data: Input data dictionary

    Returns:
        ResultModel with processed data

    Raises:
        ValidationError: If input is invalid
    """
    # Proper implementation with validation
    validated = InputModel(**input_data)
    return ResultModel(
        name=validated.name,
        value=validated.value
    )