MCPInstall

deployment

This skill should be used when the user wants to manage Railway deployments, view logs, or debug issues. Covers deployment lifecycle (remove, stop, redeploy, restart), deployment visibility (list, status, history), and troubleshooting (logs, errors, failures, crashes, why deploy failed). NOT for deleting services - use environment skill with isDeleted for that.

Installs
1K
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/railwayapp/railway-skills --skill deployment
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads deployment automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Deployment Management

Manage existing Railway deployments: list, view logs, redeploy, or remove.

Important: "Remove deployment" (railway down) stops the current deployment but keeps the service. To delete a service entirely, use the environment skill with isDeleted: true.

When to Use

  • User says "remove deploy", "take down service", "stop deployment", "railway down"
  • User wants to "redeploy", "restart the service", "restart deployment"
  • User asks to "list deployments", "show deployment history", "deployment status"
  • User asks to "see logs", "show logs", "check errors", "debug issues"

List Deployments

railway deployment list --limit 10 --json

Shows deployment IDs, statuses, and metadata. Use to find specific deployment IDs for logs or debugging.

Specify Service

railway deployment list --service backend --limit 10 --json

View Logs

Deploy Logs

railway logs --lines 100 --json

In non-interactive mode, streaming is auto-disabled and CLI fetches logs then exits.

Build Logs

railway logs --build --lines 100 --json

For debugging build failures or viewing build output.

Logs for Failed/In-Progress Deployments

By default railway logs shows the last successful deployment. Use --latest for current:

railway logs --latest --lines 100 --json

Filter Logs

# Errors only
railway logs --lines 50 --filter "@level:error" --json

# Text search
railway logs --lines 50 --filter "connection refused" --json

# Combined
railway logs --lines 50 --filter "@level:error AND timeout" --json

Time-Based Filtering

# Logs from last hour
railway logs --since 1h --lines 100 --json

# Logs between 30 and 10 minutes ago
railway logs --since 30m --until 10m --lines 100 --json

# Logs from specific timestamp
railway logs --since 2024-01-15T10:00:00Z --lines 100 --json

Formats: relative (30s, 5m, 2h, 1d, 1w) or ISO 8601 timestamps.

Logs from Specific Deployment

Deploy logs:

railway logs <deployment-id> --lines 100 --json

Build logs:

railway logs --build <deployment-id> --lines 100 --json

Get deployment ID from railway deployment list.

Note: The deployment ID is a positional argument, NOT --deployment <id>. The --deployment flag is a boolean that selects deploy logs (vs --build for build logs).

Redeploy

Redeploy the most recent deployment:

railway redeploy --service <name> -y

The -y flag skips confirmation. Useful when:

  • Config changed via environment skill
  • Need to restart without new code
  • Previous deploy succeeded but service misbehaving

Restart Container Only

Restart without rebuilding (picks up external resource changes):

railway restart --service <name> -y

Use when external resources (S3 files, config maps) changed but code didn't.

Remove Deployment

Takes down the current deployment. The service remains but has no running deployment.

# Remove deployment for linked service
railway down -y

# Remove deployment for specific service
railway down --service web -y
railway down --service api -y

This is what users mean when they say "remove deploy", "take down", or "stop the deployment".

Note: This does NOT delete the service. To delete a service entirely, use the environment skill with isDeleted: true.

CLI Options

deployment list

FlagDescription
-s, --service <NAME>Service name or ID
-e, --environment <NAME>Environment name or ID
--limit <N>Max deployments (default 20, max 1000)
--jsonJSON output

logs

FlagDescription
-s, --service <NAME>Service name or ID
-e, --environment <NAME>Environment name or ID
-d, --deploymentShow deploy logs (default, boolean flag)
-b, --buildShow build logs (boolean flag)
-n, --lines <N>Number of lines (required)
-f, --filter <QUERY>Filter using query syntax
--since <TIME>Start time (relative or ISO 8601)
--until <TIME>End time (relative or ISO 8601)
--latestMost recent deployment (even if failed)
--jsonJSON output
[DEPLOYMENT_ID]Specific deployment (optional)

redeploy

FlagDescription
-s, --service <NAME>Service name or ID
-y, --yesSkip confirmation

restart

FlagDescription
-s, --service <NAME>Service name or ID
-y, --yesSkip confirmation

down

FlagDescription
-s, --service <NAME>Service name or ID
-e, --environment <NAME>Environment name or ID
-y, --yesSkip confirmation

Presenting Logs

When showing logs:

  • Include timestamps
  • Highlight errors and warnings
  • For build failures: show error and suggest fixes
  • For runtime crashes: show stack trace context
  • Summarize patterns (e.g., "15 timeout errors in last 100 logs")

Composability

  • Push new code: Use deploy skill
  • Check service status: Use status skill
  • Fix config issues: Use environment skill
  • Create new service: Use new skill

Error Handling

No Service Linked

No service linked. Run `railway service` to select one.

No Deployments Found

No deployments found. Deploy first with `railway up`.

No Logs Found

Deployment may be too old (log retention limits) or service hasn't produced output.

FAQ

What does the deployment skill do?

This skill should be used when the user wants to manage Railway deployments, view logs, or debug issues. Covers deployment lifecycle (remove, stop, redeploy, restart), deployment visibility (list, status, history), and troubleshooting (logs, errors, failures, crashes, why deploy failed). NOT for deleting services - use environment skill with isDeleted for that.

How do I install deployment?

Run npx skills add https://github.com/railwayapp/railway-skills --skill deployment in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deployment/ (personal) or .claude/skills/deployment/ (project).

Which AI agents can use deployment?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is deployment safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains deployment?

It is published by railwayapp in railwayapp/railway-skills. It has 1,026 recorded installs.

More from railwayapp/railway-skills

View all →

use-railway

railwayapp/railway-skills

Operate Railway infrastructure: sign up for or sign in to a Railway account, create projects, provision services, databases, and buckets, deploy code, configure infrastructure as code, environments and variables, manage domains, trace requests with OpenTelemetry, troubleshoot failures, check status and metrics, manage feature flags, database recovery and HA, cloud agents, usage limits, and Railway agent tooling. Use this skill whenever the user mentions Railway, feature flags, flag rollout, targeting rules, signing up, creating an account, registering, logging in, deployments, services, environments, buckets, object storage, tracing, traces, spans, OpenTelemetry, OTLP, build failures, agent setup, MCP, or infrastructure operations, even if they don't say "Railway" explicitly. Also invoke it when the user asks to be signed up, registered, or onboarded: do not refuse — drive them through the unauthed railway up flow (deploys + signs up on the fly) or railway login (which creates acco

DevOps & Cloud8.9K installs

service

railwayapp/railway-skills

This skill should be used when the user asks about service status, wants to rename a service, change service icons, link services, or create services with Docker images. For creating services with local code, prefer the new skill. For GitHub repo sources, use new skill to create empty service then environment skill to configure source.

DevOps & Cloud1.6K installs

central-station

railwayapp/railway-skills

This skill should be used when the user asks about Central Station threads, community discussions, support questions, feature requests, or wants to search Railway's community knowledge base. Use for queries like "search central station", "find threads about", "what are people asking about", "recent support threads", or "central station topics".

1.5K installs

status

railwayapp/railway-skills

This skill should be used when the user asks "railway status", "is it running", "what's deployed", "deployment status", or about uptime. NOT for variables ("what variables", "env vars", "add variable") or configuration queries - use environment skill for those.

DevOps & Cloud1.5K installs

railway-docs

railwayapp/railway-skills

This skill should be used when the user asks about Railway features, how Railway works, or shares a docs.railway.com URL. Fetches up-to-date Railway docs to answer accurately.

Docs & Writing1K installs

deploy

railwayapp/railway-skills

This skill should be used when the user wants to push code to Railway, says "railway up", "deploy", "deploy to railway", "ship", or "push". For initial setup or creating services, use new skill. For Docker images, use environment skill.

DevOps & Cloud942 installs

Popular devops & cloud skills

View category →

microsoft-foundry

microsoft/azure-skills

Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure

OfficialDevOps & Cloud579.1K installs

azure-diagnostics

microsoft/azure-skills

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

OfficialDevOps & Cloud569.8K installs

azure-prepare

microsoft/azure-skills

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

OfficialDevOps & Cloud569K installs

azure-ai

microsoft/azure-skills

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

OfficialDevOps & Cloud568.8K installs

azure-deploy

microsoft/azure-skills

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

OfficialDevOps & Cloud568.6K installs

azure-validate

microsoft/azure-skills

Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.

OfficialDevOps & Cloud568K installs