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Zeabur Project Create

Checked
zeabur·vlatest·backend

Automatically creates new Zeabur projects with preconfigured settings based on provided templates and specifications.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add zeabur/agent-skills --skill zeabur-project-create -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

zeabur

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned zeabur/zeabur-claude-plugin at 5c8c19a65b.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
2 files, 134 lines
Copies in repo
2 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The zeabur-project-create skill allows AI agents to create new Zeabur projects. It initializes a project with a basic structure, including essential files and configurations, streamlining the initial setup process for backend development. This includes setting up a Git repository and configuring CI/CD pipelines.

When to use it

  • You need to quickly start a new backend project without manual configuration.
  • You want an AI agent to automate the creation of multiple projects with consistent setups.
  • You’re deploying code frequently and require automated CI/CD pipeline setup.
  • You're prototyping or experimenting with different backend technologies.

Key capabilities

  • Project initialization with a basic structure
  • Git repository creation and configuration
  • CI/CD pipeline configuration (details unspecified in source)
  • Automated project scaffolding

Example prompts

  • "Create a new Zeabur project named 'my-api' using Node.js."
  • "Initialize a Python backend project called 'data-processor'."
  • “Set up a Go project with the name ‘inventory-service’ and enable CI/CD.”

Tips & gotchas

The skill requires access to a Zeabur account for project creation. Specific supported languages or frameworks are not detailed in the source, so experimentation may be needed.