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Deployment Railway

Checked
forever19735·vlatest·cloud

Automates infrastructure provisioning and application deployment across environments using a configurable railway model.

Repository

Install on your platform

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

  1. 1

    Run this in your project

    terminal
    $ npx skills add forever19735/garbage --skill deployment-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

forever19735

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

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

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

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

  • Pinned to a commit: passed

    Scanned forever19735/garbage at 9b1b82baf9.

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

Commit
9b1b82baf9
Manifest
.agent/skills/deployment-railway/SKILL.md
Scanned
1 file, 62 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

This skill automates deployments using Railway, a platform that simplifies application deployment. It handles tasks like connecting to repositories, configuring environment variables, and triggering deployment pipelines based on user instructions or repository events. The tool aims to streamline the process of getting code into production quickly and reliably.

When to use it

  • Deploying a new version of a web application from a Git repository.
  • Setting up continuous integration/continuous delivery (CI/CD) for an existing project on Railway.
  • Automating the deployment of backend services or APIs.
  • Quickly deploying prototypes and testing applications to a live environment.

Key capabilities

  • Repository connection
  • Environment variable configuration
  • Deployment pipeline triggering

Example prompts

  • "Deploy my application from GitHub repository owner/repo."
  • "Set the environment variable DATABASE_URL to postgres://user:password@host:port/database for my Railway project."
  • “Trigger a deployment in Railway after pushing changes to the main branch.”

Tips & gotchas

Requires access and credentials for both your Git repository and Railway account. Ensure that the AI agent has appropriate permissions within Railway to manage deployments and environment variables.