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Railway Service

  • 286 installs
  • 30.1k repo stars
  • Updated August 4, 2026
  • davila7/claude-code-templates

railway-service is a Claude Code skill that deploys and configures Railway services, environment variables, custom domains, and health checks when shipping a backend, worker, or full-stack app to production on Railway Pa

About

railway-service is a deployment skill for Claude Code that guides developers through standing up and configuring applications on Railway PaaS. The skill covers service creation, environment variable setup, custom domain binding, and health check configuration for backends, background workers, and full-stack apps heading to production. It is built for engineers who already have runnable code and need Railway-specific wiring instead of generic Docker or Kubernetes steps. Use railway-service when you are ready to ship a service to Railway and need env vars, domains, and health endpoints configured correctly the first time.

  • Railway project and service setup
  • Environment variables and secrets wiring
  • Custom domains and networking hooks
  • Deploy commands and rollback awareness
  • Health checks and service scaling basics

Railway Service by the numbers

  • 286 all-time installs (skills.sh)
  • Ranked #341 of 1,435 DevOps & CI/CD skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/davila7/claude-code-templates --skill railway-service

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Listed on Skillselion
Installs286
repo stars30.1k
Last updatedAugust 4, 2026
Repositorydavila7/claude-code-templates

How do you deploy a service to Railway production?

Deploy and configure Railway services, env vars, domains, and health checks when shipping a backend, worker, or full-stack app to production on Railway PaaS.

Who is it for?

Full-stack and backend developers shipping Node, Python, or other services to Railway PaaS who need production env, domain, and health check setup.

Skip if: Teams deploying exclusively to AWS, GCP, or Kubernetes, or projects still in local-only prototyping with no deploy target.

When should I use this skill?

The user asks to deploy, configure, or troubleshoot a backend, worker, or full-stack app on Railway including env vars, domains, or health checks.

What you get

Railway service configuration, environment variable definitions, custom domain setup, and health check endpoints

  • Railway service config
  • Env var definitions
  • Health check setup

Files

SKILL.mdMarkdownGitHub ↗

Design to Code

High-fidelity UI restoration from Figma designs to production-ready React + TypeScript components. This SKILL uses a robust helper script to minimize manual errors and ensure pixel-perfect results.

Prerequisites

1. Figma API Token: Get from Figma → Settings → Personal Access Tokens 2. Node.js: Version 18+ 3. coderio: Installed in scripts/ folder (handled by Setup phase)

Workflow Overview

Phase 0: SETUP    → Create helper script and script environment
Phase 1: PROTOCOL → Generate design protocol (Structure & Props)
Phase 2: CODE     → Generate components and assets

---

Phase 0: Setup

Step 0.1: Initialize Helper Script

User Action: Run these commands to create the execution helper and isolate its dependencies.

mkdir -p scripts

# 1. Copy script files
# Note: Ensure you have the 'skills/design-to-code/scripts' directory available
cp skills/design-to-code/scripts/package.json scripts/package.json
cp skills/design-to-code/scripts/coderio-skill.mjs scripts/coderio-skill.mjs

# 2. Install coderio in scripts directory (adjust version if needed)
cd scripts && pnpm install && cd ..

Step 0.2: Scaffold Project (Optional)

If starting a new project:

1. Run: node scripts/coderio-skill.mjs scaffold-prompt "MyApp" 2. AI Task: Follow the instructions output by the command to create files.

---

Phase 1: Protocol Generation

Step 1.1: Fetch Data

# Replace with your URL and Token
node scripts/coderio-skill.mjs fetch-figma "https://figma.com/file/..." "figd_..."

Verify: process/thumbnail.png should exist.

Step 1.2: Generate Structure

1. Generate Prompt:

    node scripts/coderio-skill.mjs structure-prompt > scripts/structure-prompt.md

2. AI Task (Structure):

  • ATTACH: process/thumbnail.png (MANDATORY)
  • READ: scripts/structure-prompt.md
  • INSTRUCTION: "Generate the component structure JSON based on the prompt and the attached thumbnail. Focus on visual grouping. Use text content to name components accurately (e.g. 'SafeProducts', not 'FAQ')."
  • SAVE: Paste the JSON result into scripts/structure-output.json.

3. Process Result:

    node scripts/coderio-skill.mjs save-structure

Step 1.3: Extract Props (Iterative)

1. List Components:

    node scripts/coderio-skill.mjs list-components

2. For EACH component in the list:

a. Generate Prompt:

    node scripts/coderio-skill.mjs props-prompt "ComponentName" > scripts/current-props-prompt.md

b. AI Task (Props):

  • ATTACH: process/thumbnail.png (MANDATORY)
  • READ: scripts/current-props-prompt.md
  • INSTRUCTION: "Extract props and state data. Be pixel-perfect with text and image paths."
  • SAVE: Paste the JSON result into scripts/ComponentName-props.json.

c. Save & Validate:

    node scripts/coderio-skill.mjs save-props "ComponentName"
    # If this fails, re-do step 'b' with better attention to the thumbnail

---

Phase 2: Code Generation

Step 2.1: Plan Tasks

node scripts/coderio-skill.mjs list-gen-tasks

This outputs a list of tasks with indices (0, 1, 2...).

Step 2.2: Generate Components (Iterative)

For EACH task index (starting from 0):

1. Generate Prompt:

    node scripts/coderio-skill.mjs code-prompt 0 > scripts/code-prompt.md
    # Replace '0' with current task index

2. AI Task (Code):

  • ATTACH: process/thumbnail.png (MANDATORY)
  • READ: scripts/code-prompt.md
  • INSTRUCTION: "Generate the React component code. Match the thumbnail EXACTLY. Use STRICT text content from input data, do not hallucinate."
  • SAVE: Paste the code block into scripts/code-output.txt.

3. Save Code:

    node scripts/coderio-skill.mjs save-code 0
    # Replace '0' with current task index

Step 2.3: Final Integration

Inject the root component into App.tsx. Use the path found in the last task of Phase 2.1.

---

Troubleshooting

  • "Props validation failed": The AI generated empty props. Check if process/thumbnail.png was attached and visible to the AI. Retry the props generation step.
  • "Module not found": Ensure node scripts/coderio-skill.mjs save-code was run for the child component before the parent component. Phase 2 must be done in order (0, 1, 2...).
  • "Visuals don't match": Did you attach the thumbnail? The AI relies on it for spacing and layout nuances not present in the raw data.

Related skills

FAQ

What does railway-service configure on Railway?

railway-service helps developers deploy Railway services and configure environment variables, custom domains, and health checks when shipping backends, workers, or full-stack applications to production on Railway PaaS.

When should developers use railway-service?

railway-service fits when runnable application code is ready for production and the developer needs Railway-specific service setup, env configuration, domain binding, and health monitoring rather than local development help.

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