deployment

railwayapp/railway-skills · updated Apr 8, 2026

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$npx skills add https://github.com/railwayapp/railway-skills --skill deployment
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summary

View, manage, and troubleshoot Railway deployments with logs, redeploy, and removal commands.

  • List deployments and view deploy or build logs with filtering by level, text search, time range, or specific deployment ID
  • Redeploy the most recent deployment or restart containers without rebuilding to pick up external resource changes
  • Remove deployments (stops the service but keeps it intact; use the environment skill to delete services entirely)
  • Supports JSON output for all commands an
skill.md

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

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

logs

Flag Description
-s, --service <NAME> Service name or ID
-e, --environment <NAME> Environment name or ID
-d, --deployment Show deploy logs (default, boolean flag)
-b, --build Show 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)
--latest Most recent deployment (even if failed)
--json JSON output
[DEPLOYMENT_ID] Specific deployment (optional)

redeploy

Flag Description
-s, --service <NAME> Service name or ID
-y, --yes Skip confirmation

restart

Flag Description
-s, --service <NAME> Service name or ID
-y, --yes Skip confirmation

down

Flag Description
-s, --service <NAME> Service name or ID
-e, --environment <NAME> Environment name or ID
-y, --yes Skip 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.

how to use deployment

How to use deployment on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add deployment
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

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

The skills CLI fetches deployment from GitHub repository railwayapp/railway-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/deployment

Reload or restart Cursor to activate deployment. Access the skill through slash commands (e.g., /deployment) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.542 reviews
  • Xiao Chawla· Dec 20, 2024

    deployment is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aditi Mehta· Dec 16, 2024

    Keeps context tight: deployment is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kwame Ghosh· Dec 4, 2024

    Registry listing for deployment matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Isabella Gupta· Nov 23, 2024

    Keeps context tight: deployment is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Benjamin Martin· Nov 11, 2024

    deployment reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ava Huang· Nov 7, 2024

    Registry listing for deployment matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kwame Ramirez· Oct 26, 2024

    deployment reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Daniel Sharma· Oct 14, 2024

    deployment is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Benjamin Sharma· Oct 2, 2024

    Registry listing for deployment matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Isabella Srinivasan· Sep 21, 2024

    Useful defaults in deployment — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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