railway-deploy

name	railway-deploy
description	Deploy a Turbine trading bot to Railway for 24/7 cloud operation. Use after creating a bot with /create-bot.
disable-model-invocation	false
argument-hint	[bot-filename]

Turbine Bot - Railway Deployment (via GitHub)

You are helping a user deploy their Turbine trading bot to Railway for 24/7 cloud operation.

This skill uses GitHub for deployment — Railway's GitHub integration auto-deploys when a repo is connected. No Railway CLI needed.

Railway's free tier includes a $5 credit for 30 days — plenty for a lightweight Python trading bot.

Step 0: Check Prerequisites

Run these checks:

# Check gh CLI
command -v gh && gh --version || echo "GH_NOT_FOUND"

# Check gh auth status
gh auth status 2>&1 || echo "GH_NOT_AUTHENTICATED"

# Check git
command -v git && git --version || echo "GIT_NOT_FOUND"

# Check for .env
ls -la .env 2>/dev/null || echo "NO_ENV_FILE"

# Check for bot Python files in root (exclude examples/, tests/, turbine_client/)
ls *.py 2>/dev/null || echo "NO_PY_FILES"

If gh CLI is not found: Tell the user to install it:

GitHub CLI (gh) is required for deployment. Install it:
  brew install gh

Then authenticate:
  gh auth login

STOP here.

If gh is not authenticated: Tell the user:

You need to log in to GitHub first:
  gh auth login

STOP here.

If git is not found: Tell the user to install it:

Git is required. Install it:
  brew install git

STOP here.

If .env is not found: Tell the user to get set up first:

No .env file found. Run /setup first to configure your environment,
then /create-bot to generate a trading bot.

STOP here.

Step 1: Identify the Bot File

If the user passed an argument (e.g., /railway-deploy my_bot.py), use that filename.

Otherwise, look at the Python files in the project root. Find files matching bot patterns (*bot*, *trader*, *maker*, *trading*). Exclude setup.py, conftest.py, and files inside examples/, tests/, turbine_client/.

If there's exactly one candidate, confirm with the user using AskUserQuestion:

• "Which file should Railway run?" with the detected file as the recommended option

If there are multiple candidates, present them all as options.

If there are zero candidates, use AskUserQuestion with a text prompt asking for the filename.

Store the result as BOT_FILE for the remaining steps.

Step 2: Generate Deployment Configuration

Create these files using the Write tool:

requirements.txt — Railpack looks for this to install dependencies. A single . tells pip to install the package and all its deps from pyproject.toml:

.

main.py — Railpack looks for this file as the entry point. If BOT_FILE is already main.py, skip this step. Otherwise create it:

import runpy
runpy.run_path("{BOT_FILE}", run_name="__main__")

railway.toml — configures restart policy:

[deploy]
restartPolicyType = "ON_FAILURE"
restartPolicyMaxRetries = 10

Tell the user what you created and why:

• requirements.txt tells Railpack to install the project's dependencies from pyproject.toml
• main.py is the entry point Railpack auto-detects — it just runs {BOT_FILE}
• railway.toml configures restart-on-crash behavior

Step 3: Prepare for Deployment

Create a .gitignore if one doesn't already exist (or append to it if it does). Make sure these entries are present:

.env
__pycache__/
*.pyc
.venv/
venv/

IMPORTANT: Never commit .env — it contains private keys.

Create a Procfile as an alternative entry point for Railway:

web: python main.py

Stage and commit the bot file and all config files:

git add {BOT_FILE} requirements.txt main.py railway.toml .gitignore Procfile
git commit -m "Add Turbine bot for Railway deployment"

If there are other project files needed (like pyproject.toml, turbine_client/, etc.), include them too. Use your judgment — commit everything needed to run the bot, but never .env.

Step 4: Create GitHub Repo and Push

Check the current git state:

# Are we in a git repo?
git rev-parse --is-inside-work-tree 2>/dev/null || echo "NOT_A_GIT_REPO"

# Does a remote named 'origin' exist?
git remote get-url origin 2>/dev/null || echo "NO_REMOTE"

If not in a git repo:

git init
git add {BOT_FILE} requirements.txt main.py railway.toml .gitignore Procfile
git commit -m "Add Turbine bot for Railway deployment"

If a remote origin already exists: Just push:

git push origin HEAD

If no remote exists: Create a private GitHub repo and push in one step:

gh repo create turbine-bot --private --source=. --push

Verify the push succeeded by checking the exit code. If it fails, show the error and STOP.

After a successful push, get the repo URL to show the user:

gh repo view --json url -q '.url'

Step 5: Guide User to Connect Railway

Now tell the user to connect their GitHub repo to Railway. Print this clearly:

Your code is pushed to GitHub. Now connect it to Railway:

1. Go to https://railway.com/new
2. Click "Deploy from GitHub repo"
3. Select the repo: {REPO_NAME}
4. Railway will auto-deploy immediately

After the service is created, add your environment variables:

1. Click on the service in your Railway dashboard
2. Go to the "Variables" tab
3. Add the variables listed below

Then read the .env file and print the variables the user needs to set, with values masked for security. Show first 6 and last 4 characters of secret values:

Variable	Value
TURBINE_PRIVATE_KEY	0x1234...abcd
TURBINE_API_KEY_ID	abc123...wxyz
TURBINE_API_PRIVATE_KEY	secret...last4
CHAIN_ID	137 (show full value — not secret)
TURBINE_HOST	https://api.turbinefi.com (show full value — not secret)

IMPORTANT: Security handling:

• Never print full private key values. Mask them: show first 6 and last 4 characters only.
• CHAIN_ID and TURBINE_HOST are not secrets — show them in full.

Then tell the user:

Copy each value from your .env file and paste it into Railway's Variables tab.

Tip: You can also click "Raw Editor" in Railway and paste all variables at once
in KEY=VALUE format.

If API credentials are empty: Tell the user:

Your TURBINE_API_KEY_ID and TURBINE_API_PRIVATE_KEY are empty.
The bot auto-generates these on first run and saves them to .env.

Recommended: Run your bot locally first to generate credentials:
  python {BOT_FILE}

Then copy the generated values from .env into Railway's Variables tab.

Or deploy now — the bot will auto-register on Railway, but you'll need to
copy the credentials from Railway's deployment logs into the Variables tab
to persist them across redeployments.

Use AskUserQuestion:

• "API credentials are empty. What would you like to do?"
• Options: "Run bot locally first (Recommended)" / "Deploy without them"

If they choose to run locally, tell them to run python {BOT_FILE}, wait for it to register, then run /railway-deploy again. STOP here.

Step 6: Success Message

Tell the user:

Your bot is ready for Railway deployment!

What you've done:
  - Bot code pushed to GitHub
  - Connect the repo on Railway to start your bot

Future deploys are automatic:
  git add . && git commit -m "update bot" && git push
  Railway redeploys automatically on every push.

Useful links:
  Railway Dashboard  -> https://railway.com/dashboard
  Railway Logs       -> Click your service -> "Logs" tab
  GitHub Repo        -> {REPO_URL}

Railway free tier: $5 credit for 30 days, then $1/month.