railway
Railway GraphQL API (account/workspace token) for managing projects, services, deployments, environments, and variables. Use when the user mentions "Railway", "railway.com", "railway.app", deploying to Railway, managing Railway projects/services/deployments, or workspace-level Railway operations.
What this skill does
## Troubleshooting
If requests fail, run `zero doctor check-connector --env-name RAILWAY_TOKEN` or `zero doctor check-connector --url https://backboard.railway.com/graphql/v2 --method POST`.
## Authentication
Railway exposes a single GraphQL endpoint. Requests authenticate with an **account** or **workspace** token (use this skill) sent as a Bearer header:
```
Authorization: Bearer $RAILWAY_TOKEN
```
Account tokens span every workspace the user belongs to. Workspace tokens are scoped to a single workspace but expose the same query/mutation surface. For environment-scoped automation use the separate **railway-project** skill instead — it sends `Project-Access-Token` and has different scope rules.
## Environment Variables
| Variable | Description |
|---|---|
| `RAILWAY_TOKEN` | Railway account or workspace token (UUID v4 format) |
## Base URL
`https://backboard.railway.com/graphql/v2` — every operation is a `POST` to this single endpoint.
> Official docs: https://docs.railway.com/reference/public-api
## Patterns
- Every request is a `POST` with a JSON body of the form `{ "query": "...", "variables": { ... } }`.
- Write the body to `/tmp/railway_request.json` and reference it with `-d @/tmp/railway_request.json`. Never inline GraphQL strings with shell escaping.
- Railway's connection types use `edges { node { ... } }` cursor pagination.
- When you do not know the exact field name, run an introspection query first instead of guessing.
## Verify Authentication
Write to `/tmp/railway_request.json`:
```json
{
"query": "query { me { id name email } }"
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
## Discover the Schema
Use introspection to look up exact field names, argument types, and enum values before composing a real query.
Write to `/tmp/railway_request.json`:
```json
{
"query": "query Introspect($name: String!) { __type(name: $name) { name fields { name description args { name type { name kind ofType { name kind } } } type { name kind ofType { name kind } } } } }",
"variables": { "name": "Query" }
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
Re-run with `"name": "Mutation"`, `"name": "Project"`, `"name": "Service"`, etc. to drill into specific types.
## Projects
### List Projects
Write to `/tmp/railway_request.json`:
```json
{
"query": "query { projects { edges { node { id name description createdAt } } } }"
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
### Get a Project (with services and environments)
Replace `<project-id>` with the actual project ID:
Write to `/tmp/railway_request.json`:
```json
{
"query": "query GetProject($id: String!) { project(id: $id) { id name description services { edges { node { id name } } } environments { edges { node { id name } } } } }",
"variables": { "id": "<project-id>" }
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
## Deployments
### List Deployments for a Service
Replace `<project-id>`, `<environment-id>`, and `<service-id>` with the actual IDs returned by the project query above:
Write to `/tmp/railway_request.json`:
```json
{
"query": "query Deployments($input: DeploymentListInput!) { deployments(first: 20, input: $input) { edges { node { id status createdAt staticUrl meta } } } }",
"variables": {
"input": {
"projectId": "<project-id>",
"environmentId": "<environment-id>",
"serviceId": "<service-id>"
}
}
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
### Redeploy a Deployment
Replace `<deployment-id>` with the deployment to redeploy:
Write to `/tmp/railway_request.json`:
```json
{
"query": "mutation Redeploy($id: String!) { deploymentRedeploy(id: $id) { id status } }",
"variables": { "id": "<deployment-id>" }
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
### Trigger a New Deployment from Latest
Replace `<service-id>` and `<environment-id>`:
Write to `/tmp/railway_request.json`:
```json
{
"query": "mutation Trigger($serviceId: String!, $environmentId: String!) { serviceInstanceDeployV2(serviceId: $serviceId, environmentId: $environmentId) }",
"variables": {
"serviceId": "<service-id>",
"environmentId": "<environment-id>"
}
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
## Variables
### Read Variables for a Service Environment
Write to `/tmp/railway_request.json`:
```json
{
"query": "query Variables($projectId: String!, $environmentId: String!, $serviceId: String!) { variables(projectId: $projectId, environmentId: $environmentId, serviceId: $serviceId) }",
"variables": {
"projectId": "<project-id>",
"environmentId": "<environment-id>",
"serviceId": "<service-id>"
}
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
### Upsert a Variable
Write to `/tmp/railway_request.json`:
```json
{
"query": "mutation Upsert($input: VariableUpsertInput!) { variableUpsert(input: $input) }",
"variables": {
"input": {
"projectId": "<project-id>",
"environmentId": "<environment-id>",
"serviceId": "<service-id>",
"name": "FEATURE_FLAG",
"value": "enabled"
}
}
}
```
```bash
curl -s -X POST "https://backboard.railway.com/graphql/v2" --header "Authorization: Bearer $RAILWAY_TOKEN" --header "Content-Type: application/json" -d @/tmp/railway_request.json
```
## Guidelines
1. Always do an introspection query for the relevant type before building a new query — the schema evolves and Railway does not version its API.
2. Read mutations and queries return Railway-defined error objects in the top-level `errors` array; always parse and surface them rather than assuming a 200 status means success.
3. Token leak risk: never echo `$RAILWAY_TOKEN` into logs, files, or shell output.
4. For tighter blast radius on automation that only touches one project/environment, use the **railway-project** skill instead — its token is scoped and revokable per project.
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.