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Postgresql Expert

Checked
personamanagmentlayer·vlatest·database·Apache-2.0

Troubleshoot complex PostgreSQL queries, optimize performance, and design schemas with expert-level precision.

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 postgresql-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/postgresql-expert/SKILL.md
Scanned
2 files, 766 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 equips AI agents with advanced PostgreSQL database management capabilities, enabling them to execute complex queries and manage data structures efficiently. It allows agents to interact directly with the database engine for tasks ranging from schema design to performance optimization.

When to use it

  • Automating routine maintenance tasks like vacuuming tables or analyzing table statistics.
  • Generating and executing complex SQL queries for data analysis and reporting.
  • Creating, altering, or dropping database schemas and indexes dynamically.
  • Troubleshooting slow-running queries by generating optimized execution plans.

Key capabilities

  • Direct interaction with the PostgreSQL database engine.
  • Execution of advanced SQL statements including joins, subqueries, and aggregations.
  • Database schema management (CREATE, ALTER, DROP).
  • Query optimization and performance tuning assistance.
  • Data retrieval and manipulation within supported PostgreSQL versions.

Example prompts

  • "Create a new table named 'users' with columns for id, email, and created_at, then insert five sample records."
  • "Analyze the execution plan of my current SELECT query to identify why it is running slowly on large datasets."
  • "Write a complex SQL report that joins the 'orders' and 'customers' tables to calculate total revenue per region for the last quarter."

Tips & gotchas

Ensure your AI agent has the necessary read/write permissions configured in the PostgreSQL instance before attempting schema changes or data modifications. Always review generated SQL queries in a safe environment before executing them against production databases to prevent accidental data loss.