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Master programming languages for backend development. Learn language selection, fundamentals, and ecosystem for JavaScript, Python, Go, Java, C#, PHP, Ruby, and Rust.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name languages
description Master programming languages for backend development. Learn language selection, fundamentals, and ecosystem for JavaScript, Python, Go, Java, C#, PHP, Ruby, and Rust.
sasmp_version 2.0.0
bonded_agent programming-fundamentals-agent
bond_type PRIMARY_BOND
atomic_operations LANGUAGE_SELECTION, ENVIRONMENT_SETUP, PACKAGE_MANAGEMENT, VERSION_CONTROL_CONFIG
parameter_validation [object Object]
retry_logic [object Object]
logging_hooks [object Object]
exit_codes [object Object]

Programming Languages Skill

Bonded to: programming-fundamentals-agent


Quick Start

# Invoke languages skill
"Help me choose a programming language for my backend project"
"Set up Python development environment"
"Compare Go vs Rust for microservices"

Instructions

  1. Assess Requirements: Evaluate project needs (performance, scalability, team expertise)
  2. Compare Languages: Use decision matrix below
  3. Select Language: Choose based on requirements and constraints
  4. Set Up Environment: Configure IDE, package manager, linters
  5. Master Ecosystem: Learn frameworks, testing tools, deployment

Language Comparison Matrix

Language Best For Performance Learning Ecosystem
JavaScript/Node.js Real-time, Full-stack Good Easy Excellent
Python ML/AI, APIs, Scripting Moderate Easy Excellent
Go Microservices, Cloud Excellent Medium Good
Java Enterprise, Android Good Medium Excellent
C# Microsoft, Games Good Medium Good
Rust Systems, Performance Excellent Hard Growing
PHP Web, WordPress Moderate Easy Good
Ruby Web, Startups Moderate Easy Good

Decision Tree

Project Requirements?
    │
    ├─→ ML/AI/Data Science → Python
    │
    ├─→ High Performance Required?
    │     ├─→ Systems level → Rust
    │     └─→ Cloud/Microservices → Go
    │
    ├─→ Enterprise/Large Team → Java or C#
    │
    ├─→ Rapid Prototyping → Python or Ruby
    │
    └─→ Full-stack/Real-time → JavaScript/Node.js

Examples

Example 1: Language Selection

Input:  "I need to build a high-performance microservices API"
Output: Recommend Go or Rust
        - Go: Simpler, faster development, excellent concurrency
        - Rust: Maximum performance, memory safety, steeper learning curve

Example 2: Environment Setup

Input:  "Set up Python development environment"
Output:
1. Install Python 3.12+ via pyenv
2. Create virtual environment: python -m venv .venv
3. Install dependencies: pip install -r requirements.txt
4. Configure IDE (VS Code + Python extension)
5. Set up linting: ruff, mypy

Example 3: Package Management

Input:  "Configure dependency management for Node.js"
Output:
1. Initialize: npm init -y
2. Add dependencies: npm install express
3. Lock versions: package-lock.json
4. Configure .npmrc for registry

Troubleshooting

Common Issues

Issue Cause Solution
command not found Not in PATH Add to shell profile
Version mismatch Wrong version active Use version manager (nvm, pyenv)
Package conflicts Incompatible versions Use lockfile, check compatibility
Build errors Missing system deps Install required libraries

Debug Commands

# Check versions
node -v && npm -v
python --version && pip --version
go version
rustc --version && cargo --version

# Check PATH
echo $PATH | tr ':' '\n' | grep -E 'node|python|go|rust'

Test Template

# tests/test_language_selection.py
import pytest

class TestLanguageSelection:
    def test_recommends_go_for_microservices(self):
        requirements = {"type": "microservices", "performance": "high"}
        result = select_language(requirements)
        assert result["language"] in ["go", "rust"]
        assert result["confidence"] > 0.8

    def test_recommends_python_for_ml(self):
        requirements = {"type": "ml", "team_expertise": ["python"]}
        result = select_language(requirements)
        assert result["language"] == "python"

References

See references/ directory for:

  • LANGUAGE_GUIDE.md - Detailed language comparison
  • language-comparison.yaml - Structured data

Resources