clean-architecture-typescript

craftaholic/dotfiles

Implement Clean Architecture principles in TypeScript for maintainable, testable, and framework-independent applications. Use when designing new TypeScript applications, refactoring existing code, or implementing domain-centric Node.js applications.

19 stars

2 forks

4 views

View on GitHub Add to Favorites

Installation

Option 1: Use slash command in Claude Code

/install-skill https://github.com/craftaholic/dotfiles/tree/master/claude/.claude/skills/architecture/specific-language/ts

Option 2: Clone to skills directory

# Global (all projects)

git clone https://github.com/craftaholic/dotfiles/tree/master/claude/.claude/skills/architecture/specific-language/ts ~/.claude/skills/dotfiles

# Project-specific

git clone https://github.com/craftaholic/dotfiles/tree/master/claude/.claude/skills/architecture/specific-language/ts .claude/skills/dotfiles

Add MCP server to .cursor/mcp.json:

{
  "mcpServers": {
    "skillz": {
      "command": "npx",
      "args": ["-y", "skillz-mcp", "https://github.com/craftaholic/dotfiles/tree/master/claude/.claude/skills/architecture/specific-language/ts"]
    }
  }
}

Restart Cursor after adding the configuration.

Option 1: Use Gemini CLI command

gemini extensions install https://github.com/craftaholic/dotfiles/tree/master/claude/.claude/skills/architecture/specific-language/ts

Option 2: Clone to extensions directory

git clone https://github.com/craftaholic/dotfiles/tree/master/claude/.claude/skills/architecture/specific-language/ts ~/.gemini/extensions/dotfiles

Related Skills

skill-writer

Tensors and Dynamic neural networks in Python with strong GPU acceleration

docstring

Tensors and Dynamic neural networks in Python with strong GPU acceleration

at-dispatch-v2

Tensors and Dynamic neural networks in Python with strong GPU acceleration

add-uint-support

Tensors and Dynamic neural networks in Python with strong GPU acceleration