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Sql Queries

Official
anthropics·vlatest·database·Apache-2.0

This skill generates SQL queries from natural language descriptions, streamlining database interaction and simplifying data retrieval for users.

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 anthropics/knowledge-work-plugins --skill sql-queries -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

anthropics

Matched to the vendor's own GitHub organisation.

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 anthropics/knowledge-work-plugins at da38ec1ee8.

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

Scanned
1 file, 393 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 generate and execute SQL queries for interacting with relational databases. It supports query creation, data retrieval, filtering, sorting, and basic analysis using standard SQL syntax.

When to use it

  • You need to extract specific data from a database table based on certain conditions.
  • You want to perform aggregations like counting records or calculating averages.
  • Your AI agent needs to generate reports by querying structured data sources.
  • You're automating tasks that require interacting with a SQL-based backend system.

Key capabilities

  • Generate SELECT, INSERT, UPDATE, and DELETE queries
  • Filter data using WHERE clauses
  • Sort results with ORDER BY
  • Perform basic aggregations (COUNT, SUM, AVG)
  • Join multiple tables using JOIN operations

Example prompts

  • "Find all users who registered in the last 30 days."
  • "Calculate the total sales per product category from the sales table."
  • "Generate a SQL query to insert a new customer into the customers table."

Tips & gotchas

  • Ensure your AI agent has access to the correct database credentials and permissions.
  • Complex queries may require additional validation or optimization for performance.