devcontainer-setup

Generate DevContainer configurations with Dockerfile and devcontainer.json for Python 3.13 environments.

Updated Jan 23, 2026
One-click install
npx skills add https://github.com/datorresb/vibecoding-starter --skill devcontainer-setup
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: devcontainer-setup
Source: https://github.com/datorresb/vibecoding-starter/tree/main/.claude/skills/devops/devcontainer-setup
Command: npx skills add https://github.com/datorresb/vibecoding-starter --skill devcontainer-setup

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a standardized DevContainer setup to ensure consistent Python 3.13 development environments across teams, enabling reproducible builds, smoother onboarding, and fewer “works on my machine” issues.

Core Features & Use Cases

  • Environment as Code: Define development environments in code and version control, guaranteeing consistency across machines.
  • Step-by-step, configurable setup: Supports Default (all options on) or Advanced (customizable) workflows to generate Dockerfile, devcontainer.json, optional features (GitHub CLI, Docker-in-Docker, Node) and post-create automation.
  • Use Case: Use when initializing a new project, adding DevContainer support, or standardizing tool versions for a team, ensuring repeatable setup for every contributor.

Quick Start

Choose Default or Advanced, then run Steps 1-7 exactly as described in this skill to produce a ready-to-run DevContainer scaffold in your project root.

Frequently Asked Questions about devcontainer-setup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I standardize Python DevContainers across my development team?▼

Standardize Python DevContainers by generating environment-as-code configurations, including Dockerfile and devcontainer.json, ensuring reproducible builds and consistent setups across all machines.

What is the process for setting up a DevContainer for a new Python project?▼

Setting up a DevContainer involves following a strict step-by-step process to scaffold a Dockerfile, devcontainer.json, optional features, and post-create automation directly in your project root.

Can I customize optional features like Docker-in-Docker when creating a devcontainer.json?▼

Yes, you can customize optional features like Docker-in-Docker, GitHub CLI, and Node by selecting the Advanced workflow, which allows configurable setup instead of the Default all-options-on mode.

Does this DevContainer setup handle secrets and post-create automation?▼

Yes, the DevContainer setup handles secrets and includes post-create automation, enforcing a strict configuration process that records changes without introducing unlisted modifications to your environment.

What is the best way to fix "works on my machine" issues for Python developers?▼

Fix works on my machine issues by using DevContainer configurations to define development environments in code and version control, guaranteeing Python 3.13 environment consistency across contributors.

When should I not use an automated DevContainer setup for my project?▼

Avoid automated DevContainer setup when your project requires changes outside the enforced step-by-step process, as this approach records configurations strictly without introducing unlisted modifications.