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Using Relational Databases

Listed
ancoleman·vlatest·database·MIT

This skill enables interacting with relational databases to query and manipulate data, streamlining data access and analysis 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 ancoleman/ai-design-components --skill using-relational-databases -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 failed 2 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: get.tur.so.

    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.

    Hosts contacted

    get.tur.soundeclared

    What it found

    • skills/using-relational-databases/references/serverless-databases.md:270contacts get.tur.so
      curl -sSfL https://get.tur.so/install.sh | bash
    • skills/using-relational-databases/references/sqlite-guide.md:119contacts get.tur.so
      curl -sSfL https://get.tur.so/install.sh | bash

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 2 places.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

    What it found

    • skills/using-relational-databases/references/serverless-databases.md:270remote script piped into a shell
      curl -sSfL https://get.tur.so/install.sh | bash
    • skills/using-relational-databases/references/sqlite-guide.md:119remote script piped into a shell
      curl -sSfL https://get.tur.so/install.sh | bash

  • 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 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.

  • 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/using-relational-databases/SKILL.md
Scanned
17 files, 5,912 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 interact with and retrieve data from relational databases. It allows for querying, filtering, and potentially updating information stored in structured tables. The agent can formulate SQL queries based on natural language requests or predefined schemas.

When to use it

  • Data Extraction: Retrieve specific customer details from a CRM database based on a description ("Find all customers in California who purchased product X").
  • Report Generation: Create summaries of data stored in tables, such as sales figures by region or average order value.
  • Inventory Management: Check stock levels and update inventory records within a database system.
  • Data Validation: Verify the integrity of data by querying for inconsistencies or errors based on defined rules.

Key capabilities

  • SQL query generation
  • Database interaction
  • Data retrieval from relational tables
  • Filtering and sorting data

Example prompts

  • "What are the names of all products with a price greater than $50?"
  • "Show me the total sales for each region in the last quarter."
  • "Update the quantity on hand for product ID 123 to 10."

Tips & gotchas

The agent's performance depends heavily on the clarity and accuracy of the database schema. Providing a clear description or sample data can significantly improve query results.