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Postgres

Official
planetscale·vlatest·database·MIT

Connects to and executes SQL queries against your PlanetScale PostgreSQL databases directly within the AI workflow.

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 planetscale/database-skills --skill postgres -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

planetscale

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 planetscale/database-skills at 73b20b7eb6.

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

Commit
73b20b7eb6
Manifest
skills/postgres/SKILL.md
Scanned
23 files, 1,186 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

The PostgreSQL skill enables AI agents to interact with PostgreSQL databases, including querying data, managing schemas, and executing administrative tasks. It supports common SQL operations such as SELECT, INSERT, UPDATE, and DELETE, along with advanced features like transaction handling and query optimization.

When to use it

  • You need to retrieve or manipulate structured data stored in a PostgreSQL database.
  • Your application requires dynamic querying of relational data for reporting or analytics.
  • You are automating database maintenance tasks such as backups or schema migrations.

Key capabilities

  • Execute SQL queries against PostgreSQL databases
  • Manage database schemas and tables
  • Handle transactions and ensure data integrity
  • Perform basic administrative operations like user management

Example prompts

  • "Run a SELECT query to retrieve all users from the 'users' table."
  • "Insert a new record into the 'orders' table with the following details: order_id=100, customer_id=5, total_amount=25.99."
  • "Optimize the performance of the 'products' table by adding an index on the 'category' column."

Tips & gotchas

  • Ensure that your AI agent has proper authentication credentials and access permissions to interact with the PostgreSQL instance.
  • Be cautious when executing write operations (e.g., INSERT, UPDATE, DELETE) in production environments—always test queries first or use a transaction block.