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Postgres Query Expert

Checked
ratacat·vlatest·database

Helps with PostgreSQL, querying as part of working with databases and data persistence 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 ratacat/claude-skills --skill postgres-query-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

ratacat

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 ratacat/claude-skills at d4b471d05d.

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

Commit
d4b471d05d
Manifest
skills/postgres-query-expert/SKILL.md
Scanned
1 file, 230 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 postgres-query-expert skill enables AI agents to execute complex PostgreSQL queries directly, transforming natural language requests into valid SQL statements for data retrieval and manipulation. It acts as a specialized interface allowing agents to interact with database schemas without requiring manual code generation or syntax verification from the user.

When to use it

  • Retrieving specific records based on natural language descriptions of business logic.
  • Generating aggregate reports that require multiple joins and conditional filtering.
  • Validating data integrity by running diagnostic queries against production tables.
  • Automating routine administrative tasks like updating status fields across large datasets.

Key capabilities

  • Translates natural language prompts into executable PostgreSQL SQL code.
  • Handles complex query structures including joins, subqueries, and aggregations.
  • Operates within the context of a connected PostgreSQL database instance.

Example prompts

  • "Find all customers who have placed orders in the last 30 days but haven't made a purchase this month."
  • "Generate a report showing total revenue per category, grouped by region and sorted by highest sales volume."
  • "Update the status of all pending support tickets to 'resolved' where the resolution time is less than 24 hours."

Tips & gotchas

Ensure your AI agent has explicit read/write permissions on the target PostgreSQL database before executing write operations. Always review generated SQL queries in a sandbox environment before running them against production data to prevent accidental data loss or performance bottlenecks.