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Sql Expert

Checked
personamanagmentlayer·vlatest·database·Apache-2.0

The SQL Expert skill generates complex SQL queries from natural language descriptions, streamlining database interactions and boosting developer efficiency.

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 personamanagmentlayer/pcl --skill sql-expert -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

personamanagmentlayer

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 personamanagmentlayer/pcl at 79ccaa9820.

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

Commit
79ccaa9820
Manifest
stdlib/data/sql-expert/SKILL.md
Scanned
2 files, 850 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

The SQL Expert skill empowers AI agents to execute complex database operations directly, including writing queries, analyzing data structures, and performing transformations without manual code intervention. It bridges the gap between natural language requests and raw database interactions, enabling autonomous data retrieval and manipulation.

When to use it

  • Automating routine reporting tasks that require aggregating data from multiple tables.
  • Investigating data anomalies by generating diagnostic queries on the fly.
  • Extracting specific datasets for downstream analysis or export without writing custom scripts.
  • Validating data integrity by running checks against existing database schemas.

Key capabilities

  • Generates and executes SQL queries based on natural language instructions.
  • Interprets database schema information to construct accurate joins and filters.
  • Performs data aggregation, sorting, and grouping operations efficiently.
  • Handles complex query logic involving subqueries and conditional statements.

Example prompts

  • "Find all customers who have placed orders in the last 30 days but haven't made a purchase in the current month."
  • "Generate a report showing total sales revenue broken down by region and product category for Q1."
  • "Identify any duplicate entries in the user table based on email addresses and list them."

Tips & gotchas

Ensure your AI agent has read-only permissions or appropriate write access configured before executing modification queries to prevent accidental data loss. Always verify the generated SQL logic against your specific database dialect (e.g., PostgreSQL vs. MySQL) as syntax can vary slightly between systems.