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Db Infra Mocks

Checked
pilinux·vlatest·testing·MIT

Simulates database infrastructure changes for testing, streamlining development and reducing deployment risks.

Repository

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 pilinux/gorest --skill db-infra-mocks -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

pilinux

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 pilinux/gorest at 38aab64fc2.

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

Commit
38aab64fc2
Manifest
.agents/skills/db-infra-mocks/SKILL.md
Scanned
1 file, 50 lines
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

This skill allows AI agents to generate mock database infrastructure configurations. It can produce realistic examples of databases, tables, and related objects based on provided specifications or prompts. The generated configurations are useful for development, testing, and demonstration purposes where a real database is not required or feasible.

When to use it

  • Development Environments: Quickly create sample database schemas for local development without setting up a full database instance.
  • Testing Scenarios: Generate mock data structures to test application logic in isolation.
  • Proof of Concepts (POCs): Demonstrate how an application would interact with a database without the overhead of deploying one.
  • Training and Education: Illustrate database design principles by generating example configurations.

Key capabilities

  • Generates mock database infrastructure configurations.
  • Supports various database types (implied, not explicitly listed).
  • Creates realistic examples of databases, tables, and objects.

Example prompts

  • "Generate a mock PostgreSQL schema for an e-commerce application."
  • "Create a sample MySQL database with tables for users and products."
  • “Give me a mock MongoDB configuration for a blog.”

Tips & gotchas

The quality of the generated configurations depends heavily on the clarity and specificity of the prompt. Providing details about desired table structures, data types, or relationships will yield more useful results.