Community skillDraft — source instructions not independently live-testedData & infrastructure

Railway for Meta Muse

List projects and deployments, set variables, redeploy.

Read and write the user's Railway infrastructure through the Railway GraphQL API: list projects, inspect a project, list deployments, set environment variables, and redeploy deployments. Use when the user mentions Railway or deployments they host there.

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How to set it up

Paste a prompt

Draft — these instructions come from the linked source and have not been independently live-tested by OpenTools.

Before you start

  • API token (account or workspace)

Steps

  1. Paste the install prompt into a chat with Muse.
  2. Muse fetches the pinned SKILL.md and the 2 files in its manifest.
  3. Authorize your own account through Muse’s secure credential flow.
  4. Have Muse run the status check shown in the source skill.

Prompt to paste into Muse

Install this connector: https://raw.githubusercontent.com/bluman1/muse-connectors/6e31fd44a71f9f28377a1460e64cd7483c3cce22/connectors/railway/SKILL.md
Read its Files manifest and install exactly those files. Collect credentials through Muse's secure credential flow; never ask me for raw keys in chat. Run the skill's status check and report the result.

Account access: account or workspace Bearer token via the secure credential flow (`credentials.request_api_access`); created in the Railway dashboard under Tokens. Note: project tokens are a different mechanism (they use a `Project-Access-Token` header instead of `Authorization: Bearer`) and are out of scope for this CLI.

Allowed hosts: backboard.railway.com

Confirm it works: `bin/railway.py auth` (must return `"ok": true`)

Services it connects with

These are the services the connector uses. The publisher is identified separately.

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