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railway-deployment

Deep knowledge about deploying applications to Railway (PaaS, Docker, Nixpacks).

Install

mkdir -p .claude/skills/railway-deployment-mayarid && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13635" && unzip -o skill.zip -d .claude/skills/railway-deployment-mayarid && rm skill.zip

Installs to .claude/skills/railway-deployment-mayarid

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Deep knowledge about deploying applications to Railway (PaaS, Docker, Nixpacks).
80 charsno explicit “when” trigger

About this skill

Context

Deploying {{project_name}} ({{project_type}}) to Railway. You will follow a strict 6-phase Deployment Lifecycle Contract.

Instructions

Execute the following phases in order:

Phase 1: Authentication

  1. Ensure the RAILWAY_TOKEN environment variable is set to a valid project token.
  2. If running locally, authenticate interactively with railway login. For automated agents, ensure the token is provided.
  3. Validate by running railway status to confirm the active project and environment.

Phase 2: Build

  1. Railway typically handles the build process remotely using Nixpacks or a Dockerfile.
  2. Ensure your railway.toml or Dockerfile is correctly configured in the project root.
  3. Local building is not usually required for a standard Railway deploy, but you may run local build scripts (e.g., npm run build) if generating static assets before pushing.

Phase 3: Install / Provisioning

  1. Ensure the target Railway project and service exist.
  2. If the project isn't linked, run railway link (requires interactive selection or specific project ID flags).
  3. If necessary, provision databases or other services via the Railway dashboard or CLI (e.g., railway run for migrations).

Phase 4: Deploy

  1. Ship the artifact to Railway.
  2. Run railway up --detach to deploy the current directory to the linked project and service. The --detach flag prevents the CLI from tailing logs indefinitely.

Phase 5: Checking

  1. Verify the deployment was successful.
  2. Run railway status to check if the service is deployed and running.
  3. Retrieve the public URL (often via the dashboard or railway domain) and use curl -sSf <URL> to ensure the application returns a 200 OK status code.
  4. If it fails, inspect logs using railway logs.

Phase 6: Update / Rollback

  1. If Phase 5 fails, immediately initiate a rollback.
  2. Railway supports reverting to previous deployments via the dashboard or by triggering a redeploy of an older Git commit if connected to GitHub.
  3. Note the failure in the progress log.

Validation

  • Railway authentication (railway status) succeeds.
  • Remote build succeeds (indicated by a successful deploy).
  • Service is up and running.
  • Health check (curl) returns 200 OK.

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