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Architecting Data

Checked
ancoleman·vlatest·database·MIT

Designs efficient data structures and pipelines to organize, store, and access information effectively.

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 ancoleman/ai-design-components --skill architecting-data -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

ancoleman

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 ancoleman/ai-design-components at 76551b7b19.

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

Commit
76551b7b19
Manifest
skills/architecting-data/SKILL.md
Scanned
14 files, 3,048 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 enables AI agents to design data architectures, including defining schemas for relational databases and NoSQL stores. It can generate SQL scripts for creating tables and indexes, as well as suggest appropriate data types and constraints. The agent can also propose optimal indexing strategies to improve query performance.

When to use it

  • You need a database schema designed for a new application or feature.
  • You're migrating data between different database systems (e.g., relational to NoSQL).
  • Existing queries are slow, and you suspect the database indexes are not optimal.
  • You want to define a data model that supports specific analytical requirements.

Key capabilities

  • Schema design for relational databases
  • Schema design for NoSQL stores
  • Generation of SQL scripts (CREATE TABLE, CREATE INDEX)
  • Data type and constraint recommendations
  • Indexing strategy suggestions

Example prompts

  • "Design a database schema to store customer order information, including products, quantities, and shipping addresses."
  • "I'm moving from PostgreSQL to MongoDB. Can you design a NoSQL schema that mirrors my existing relational data?"
  • "My query for retrieving recent orders is slow. Suggest some indexes I could add to improve performance."

Tips & gotchas

The agent’s output should be reviewed by a database administrator or experienced developer, as it may require adjustments based on specific environment and operational considerations. Providing context about existing systems or data volumes will help the agent generate more relevant suggestions.