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code-generator

code-generator

github.com/partme-aiDevelopment716123 installsUpdated 3w ago
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About code-generator

code-generator is a developer skill for generating documented code, project scaffolds, and boilerplate, as well as restructuring existing code. It emphasizes error handling, language conventions, and tests across five languages.

Key features

  1. 01Generate functions, classes, and modules
  2. 02Scaffold project structure and configuration
  3. 03Create CRUD boilerplate
  4. 04Refactor code structure
  5. 05Support five languages and tests

Use cases

  1. 01Generate typed code for a new feature
  2. 02Set up a TypeScript project structure
  3. 03Add happy-path and error-path tests

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/partme-ai/full-stack-skills --skill code-generator

After installing, type/code-generatorin Claude Code to confirm it loaded.

Details

From the project README

When to use this skill

Use this skill whenever the user wants to:

  • Generate functions, classes, or modules with proper documentation and error handling
  • Scaffold a new project with configuration files and directory structure
  • Create boilerplate code (CRUD controllers, service layers, data models)
  • Refactor or optimize existing code structure
  • Generate code from templates or specifications

How to use this skill

Workflow
  1. Clarify requirements - Identify the target language, framework, and coding conventions
  2. Choose the generation type - Function/class, module/package, or full project scaffold
  3. Generate code - Produce complete, documented, tested code following the patterns below
  4. Validate output - Ensure the code compiles/runs and follows project conventions
Code Generation Patterns

Function generation (Python example):

def calculate_order_total(
    items: list[OrderItem],
    discount_pct: float = 0.0,
    tax_rate: float = 0.08,
) -> Decimal:
    """Calculate the total price for an order including tax and discount.

    Args:
        items: List of order items with price and quantity.
        discount_pct: Discount percentage (0.0 to 1.0).
        tax_rate: Tax rate to apply after discount.

    Returns:
        Final order total as a Decimal rounded to 2 places.

    Raises:
        ValueError: If discount_pct is not between 0 and 1.
    """
    if not 0 <= discount_pct <= 1:
        raise ValueError(f"discount_pct must be 0-1, got {discount_pct}")

    subtotal = sum(item.price * item.quantity for item in items)
    discounted = subtotal * Decimal(1 - discount_pct)
    total = discounted * Decimal(1 + tax_rate)
    return total.quantize(Decimal("0.01"))

Project scaffold (TypeScript/Node):

my-service/
├── src/
│   ├── controllers/    # Route handlers
│   ├── services/       # Business logic
│   ├── models/         # Data models / DTOs
│   ├── middleware/      # Auth, logging, error handling
│   └── index.ts        # Entry point
├── tests/
│   ├── unit/
│   └── integration/
├── package.json
├── tsconfig.json
└── README.md
Supported Languages
  • Python (with type hints, docstrings, pytest)
  • JavaScript / TypeScript (ESM, JSDoc or TSDoc)
  • Java (JavaDoc, Maven/Gradle)
  • Go (godoc, modules)
  • Rust (rustdoc, Cargo)

Best Practices

  1. Always include error handling - Validate inputs, use typed exceptions, return meaningful error messages
  2. Add documentation - Every public function/class gets a docstring with params, returns, and raises
  3. Follow language conventions - PEP 8 for Python, gofmt for Go, Prettier for TypeScript
  4. Generate tests alongside code - At minimum, one happy-path and one error-path test per function
  5. Use type annotations - Catch bugs early with static typing where the language supports it

Keywords

代码生成, code generation, scaffold, boilerplate, template, 函数, 类, 模块, project structure, code scaffold, 项目脚手架

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