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Railway Deploy

作者 dbanys · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
1378
总下载
0
收藏
3
当前安装
1
版本数
在 OpenClaw 中安装
/install railway-deploy
功能描述
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.
安全使用建议
This skill appears to be a straightforward Railway CLI deploy helper, but before installing or letting an agent use it: 1) Ensure the runtime has the Railway CLI installed and you understand which Railway account/token the agent will use—the skill itself doesn't declare credentials. 2) The skill's commands can edit environment variables, mark services/volumes deleted, and otherwise mutate project state—limit the agent's Railway account permissions or require human confirmation for destructive actions. 3) If you don't trust automatic runs, require the agent to ask for explicit approval before running `railway` commands or test in a separate project/account with limited privileges.
功能分析
Type: OpenClaw Skill Name: railway-deploy Version: 1.0.0 The skill is classified as suspicious due to the broad `allowed-tools: Bash(railway:*)` permission granted in `SKILL.md`. While the instructions themselves are benign and focused on legitimate deployment actions, this permission, combined with the instruction to use user-provided input for commit messages (e.g., `railway up -m "<MSG>"`), creates a significant risk of shell injection if the AI agent's implementation does not properly sanitize user input before executing `railway` CLI commands. This represents a critical vulnerability rather than clear evidence of intentional malicious behavior within the skill definition itself.
能力评估
Purpose & Capability
The SKILL.md clearly implements a 'deploy to Railway' helper (uses `railway up`, environment edits, service targeting). However the registry metadata declares no required binaries or credentials while the instructions explicitly call `railway` CLI commands and show examples that modify projects/environments. The missing declared dependency on the Railway CLI and the lack of any declared primary credential is a minor incoherence: the skill will only work (and be able to act) if a Railway CLI is present and authenticated.
Instruction Scope
Instructions are focused on deploying and related tasks (detach/CI modes, target service/project, streaming logs). They also include commands that edit environment config (`railway environment edit --json`), set/delete variables, and mark services/volumes as deleted. Those are legitimate for a deployment skill but are high‑privilege actions — the SKILL.md gives the agent authority to change or delete Railway resources if the agent's CLI session has permissions. The skill does not instruct the agent to read unrelated local files or to exfiltrate data to unexpected endpoints.
Install Mechanism
Instruction-only skill with no install spec or code files. This lowers risk because nothing is downloaded or written to disk by the skill package itself.
Credentials
The skill declares no required environment variables or primary credential, yet operation depends on an authenticated Railway CLI session (or a Railway token available in the runtime). The reference docs mention many Railway/Railpack environment variables (RAILPACK_*, RAILWAY_*) but those are configuration values used by Railway — the skill itself does not declare or request secrets. Users should be aware that the agent will act with whatever Railway account/credentials are already present in its environment.
Persistence & Privilege
always:false and no install scripts — the skill does not request permanent inclusion or system-level modification. Autonomous invocation is allowed (platform default); combined with the skill's ability to change/delete projects, that means an agent invoked by this skill could act without extra prompts if the platform allows it, but that is a normal deployment plugin behavior rather than an inherent incoherence.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install railway-deploy
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /railway-deploy 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of the deploy skill for Railway. - Enables code deployment to Railway using `railway up`, with detailed CLI usage instructions. - Supports both detach (default) and CI (log streaming) deploy modes, including when to use each. - Provides guidance on commit messages, environment selection, and handling unlinked projects. - Describes common errors and how to resolve them. - Lists related skills for status checks, logs, and environment/config changes after deploy.
元数据
Slug railway-deploy
版本 1.0.0
许可证
累计安装 3
当前安装数 3
历史版本数 1
常见问题

Railway Deploy 是什么?

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. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1378 次。

如何安装 Railway Deploy?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install railway-deploy」即可一键安装,无需额外配置。

Railway Deploy 是免费的吗?

是的,Railway Deploy 完全免费(开源免费),可自由下载、安装和使用。

Railway Deploy 支持哪些平台?

Railway Deploy 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Railway Deploy?

由 dbanys(@dbanys)开发并维护,当前版本 v1.0.0。

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