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Deployment

Listed
railwayapp·vlatest·devops·MIT

Automates railwayapp application deployments to various environments, ensuring consistent releases and reduced manual effort.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it use-railway, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add railwayapp/railway-skills --skill use-railway -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

railwayapp

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 3 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 3 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: backboard.railway.com, railway.com, station-server.railway.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    railway.comundeclaredstation-server.railway.comundeclaredbackboard.railway.comundeclared

    What it found (3 of 8)

    • plugins/railway/skills/use-railway/SKILL.md:142contacts railway.com
      bash <(curl -fsSL https://railway.com/install.sh) --agents -y # Install CLI and configure detected agents
    • plugins/railway/skills/use-railway/SKILL.md:143contacts railway.com
      bash <(curl -fsSL https://railway.com/install.sh) # Shell script (macOS, Linux, Windows via WSL)
    • plugins/railway/skills/use-railway/references/request.md:44contacts station-server.railway.com
      curl -s 'https://station-server.railway.com/gql' \
  • No credential access: failed

    Touches credential material in 5 places.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

    What it found (3 of 5)

    • plugins/railway/skills/use-railway/references/analyze-db.md:117SSH private keys or config
      ls ~/.ssh/*.pub 2>/dev/null  # list local public keys
    • plugins/railway/skills/use-railway/references/analyze-db.md:126SSH private keys or config
      Local keys available:    <list from ~/.ssh/*.pub, or "none">
    • plugins/railway/skills/use-railway/references/analyze-db.md:131SSH private keys or config
      3. Generate a new key  — `ssh-keygen -t ed25519 -f ~/.ssh/id_ed25519_railway`
  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 3 places.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

    What it found

    • plugins/railway/skills/use-railway/SKILL.md:141remote script piped into a shell
      curl -fsSL agents.railway.com | sh # Install CLI and configure detected agents
    • plugins/railway/skills/use-railway/SKILL.md:142remote script run via process substitution
      bash <(curl -fsSL https://railway.com/install.sh) --agents -y # Install CLI and configure detected agents
    • plugins/railway/skills/use-railway/SKILL.md:143remote script run via process substitution
      bash <(curl -fsSL https://railway.com/install.sh) # Shell script (macOS, Linux, Windows via WSL)
  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • Pinned to a commit: passed

    Scanned railwayapp/railway-skills at f48070c954.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
26 files, 12,146 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The deployment skill automates the process of deploying applications to production environments, handling tasks like building, packaging, and launching services. It supports multiple platforms and integrates with CI/CD pipelines to streamline release workflows.

When to use it

  • Deploying a new version of an application after code changes are merged into the main branch.
  • Setting up continuous deployment for microservices in a cloud-native architecture.
  • Automating the rollout of updates across staging, testing, and production environments.

Key capabilities

  • Integration with CI/CD tools like GitHub Actions and GitLab CI.
  • Support for containerized deployments using Docker and Kubernetes.
  • Automated rollback mechanisms in case of deployment failures.

Example prompts

  • "Deploy my app to the staging environment using the latest commit from the develop branch."
  • "Set up a CI/CD pipeline that triggers a deployment on every merge to main."
  • "Roll back the last deployment due to an error in the production environment."

Tips & gotchas

  • Ensure your infrastructure and environment configurations are version-controlled for consistency.
  • Monitor deployment logs closely, as automated processes can fail silently if not properly configured.