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Database Architect

Checked
omer-metin·vlatest·database·Apache-2.0

Designs, optimizes, and troubleshoots relational databases based on provided data schemas and performance requirements.

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 omer-metin/skills-for-antigravity --skill database-architect -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

omer-metin

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 omer-metin/skills-for-antigravity at e8dcf4e873.

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

Scanned
4 files, 848 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 design and architect database solutions. It can generate relational schemas, including tables, columns, data types, and relationships, based on given requirements. The agent is also capable of suggesting appropriate indexing strategies for optimal query performance.

When to use it

  • You need a new database schema designed from scratch for an application.
  • You want to optimize existing database queries by identifying missing indexes.
  • You're migrating data between different database systems and require schema translation assistance.
  • You’re exploring different database technologies (e.g., relational vs. NoSQL) and need guidance on selecting the best fit for a project.

Key capabilities

  • Relational schema generation
  • Table, column, and data type definition
  • Relationship modeling (one-to-many, many-to-many)
  • Indexing strategy recommendations

Example prompts

  • "Design a database schema for an online bookstore."
  • "Suggest indexes to improve the performance of this SQL query: [query text]"
  • "What are the pros and cons of using PostgreSQL versus MySQL for a high-traffic e-commerce site?"

Tips & gotchas

The agent's output is based on its training data, so it’s helpful to provide clear and detailed requirements. Review generated schemas carefully as they may require adjustments based on specific application needs.