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Database Design Patterns

Checked
nickcrew·vlatest·database·MIT

Helps with database, design, patterns as part of working with databases and data persistence workflows.

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 nickcrew/claude-cortex --skill database-design-patterns -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

nickcrew

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 nickcrew/claude-ctx-plugin at bb47af79ad.

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

Commit
bb47af79ad
Manifest
skills/database-design-patterns/SKILL.md
Scanned
7 files, 929 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 apply established database design patterns, such as sharding, denormalization, and eventual consistency. It helps optimize database performance, scalability, and data availability by suggesting appropriate architectural choices based on specific use case requirements. The agent can analyze a problem description and recommend suitable pattern implementations or modifications.

When to use it

  • Scaling an existing database: When your current database is struggling with increased load or data volume.
  • Designing a new application's database: To proactively address performance and scalability concerns from the outset.
  • Optimizing query performance: When queries are slow, and you suspect inefficient data structures or relationships.
  • Dealing with high availability requirements: When minimizing downtime and ensuring data redundancy is critical.

Key capabilities

  • Pattern Recommendation: Suggests appropriate database design patterns based on problem descriptions.
  • Implementation Guidance: Provides advice on how to implement selected patterns.
  • Trade-off Analysis: Explains the pros and cons of different pattern choices.
  • Modification Suggestions: Recommends adjustments to existing designs for improved performance or scalability.

Example prompts

  • "I need to design a database for a social media platform with millions of users and posts. What patterns should I consider?"
  • "My e-commerce site's product catalog is too large, leading to slow search times. How can I improve this using database design patterns?"
  • “We’re experiencing frequent downtime on our primary database server. Suggest a solution involving database design patterns.”

Tips & gotchas

  • The agent requires a clear description of the problem and desired outcomes for effective pattern recommendations. Vague requests will yield less useful results.