Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/onsager-ai/dev-skillsnpx agentmods add skills/onsager-ai/dev-skills/railwayWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/onsager-ai/dev-skills/railway)<a href="https://agentmods.dev/skills/onsager-ai/dev-skills/railway"><img src="https://agentmods.dev/badge/skills/onsager-ai/dev-skills/railway.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00289 | $0.05467 |
| Opus 5 | $0.00144 | $0.02733 |
| Sonnet 5 | $0.00058 | $0.01093 |
| Haiku 4.5 | $0.00029 | $0.00547 |
Grade A, and why
railway scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(railway:*), Bash(npm install -g @railway/cli:*), Bash(which railway), Bash(jq:*), Bash(sh *), Bash(bash *), Bash(curl *), Bash(agent-browser:*), Bash(npx agent-browser:*), Bash(just *), Read, Write, E How it starts
The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.
railway
One skill for the full Railway operator loop: status → debug → fix → deploy → verify. It wraps the railway CLI in a non-interactive, JSON-first style that an agent can drive without prompts, and it leans on RAILWAY_TOKEN from the environment instead of an interactive railway login.
This skill is repo-agnostic. It assumes the project is hosted on Railway (railway.com) and that a RAILWAY_TOKEN is exported in the environment. It makes no assumptions about the stack (Node, Python, Go, Docker, Nixpacks/Railpack — Railway's builder figures it out).
When this skill triggers
Phrases that should route here:
- Deploy / build
- "deploy this to railway"
- "push to railway", "ship to railway", "railway up"
- "build is failing on railway", "why did my build fail"
- Logs / debugging
- "show me the railway logs", "tail the logs", "railway logs --since 1h"
- "why is my service crashing on railway"
- "show me the 500s on railway", "show http logs", "show slow requests"
- "find the request id abc123 in railway logs"
- Ops
- "redeploy on railway", "restart the api service", "roll back the last deploy"
- "scale my railway service", "remove the latest deployment"
- State / discovery
- "list my railway projects", "what services are in this project", "list deployments"
- "what's the status of my railway project", "is my service healthy"
- Variables
- "set a railway env var FOO=bar", "list railway variables", "delete a railway var"
- Run / connect
- "run this script with railway production env", "open a shell with railway env"
- "ssh into my railway service", "connect to my railway postgres / redis / mongo"
- Metrics
- "what's the cpu/memory on railway", "is my service hitting limits"
- "p95 latency on railway", "request rate on /api"
Skip when:
- The host is not Railway (Fly, Render, Vercel, AWS, …). This skill knows the
railwayCLI; it does not generalise. - The fix is a code change with no operational lever — let the normal dev-process skills handle the code; come back here once it's time to deploy or read logs.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 347 lines · 289 tokens per session scan A 85ffb1592b3f
railway is a skill published in the GitHub repository onsager-ai/dev-skills (5 stars, last pushed 27d ago), licensed MIT. It adds 289 tokens to every session and 5,467 once invoked, about $0.0014 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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