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Scalable Data Schema

Checked
sunnypatneedi·vlatest·database

Helps with data, schema design as part of agent workflows 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 sunnypatneedi/claude-starter-kit --skill scalable-data-schema -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

sunnypatneedi

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 sunnypatneedi/claude-starter-kit at bb46cf5d4f.

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

Commit
bb46cf5d4f
Manifest
skills/engineering/scalable-data-schema/SKILL.md
Scanned
1 file, 551 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 define and manage data schemas that can evolve over time. It supports adding new fields, changing data types, and handling backward compatibility when updating a schema. The agent can then use these schemas for structured data storage, retrieval, and validation.

When to use it

  • Building a knowledge base: Define a schema for storing facts about entities (e.g., people, places, events) that needs to be updated as new information becomes available.
  • Creating a product catalog: Manage the structure of product data, easily adding attributes like color or size without breaking existing records.
  • Processing user input: Define schemas for structured forms or questionnaires and validate user responses against them.
  • Managing logs: Create flexible schemas to capture different types of log events with varying fields.

Key capabilities

  • Schema definition (specifying field names, data types)
  • Schema evolution (adding/removing fields)
  • Backward compatibility handling
  • Data validation based on schema rules

Example prompts

  • "Define a schema for 'customer' with fields: name (string), email (string), and order_total (number)."
  • "Add a new field 'address' to the customer schema, making it an object containing street, city, and zip code."
  • “Update the ‘order_total’ field in the customer schema from number to decimal.”

Tips & gotchas

This skill requires some understanding of data structures and schema design principles. Be mindful of potential breaking changes when evolving schemas; careful planning is needed for backward compatibility.