Skip to content
TrustedSkillsbeta
Back to all skills

Postgresql

Listed
2025emma·vlatest·database·MIT

Connects to and queries PostgreSQL databases using optimized SQL generation and data retrieval capabilities.

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 2025emma/vibe-coding-cn --skill postgresql -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

2025emma

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    SKILL.md has no YAML frontmatter, so it declares nothing machine-readable.

    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 2025emma/vibe-coding-cn at 9b42dd10dd.

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

Commit
9b42dd10dd
Manifest
i18n/en/skills/postgresql/SKILL.md
Scanned
6 files, 4,201 lines
Copies in repo
2 — all of them scanned
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 PostgreSQL skill enables AI agents to interact with and manage PostgreSQL database instances directly. It facilitates tasks such as executing SQL queries, managing schemas, and performing administrative operations within the database environment.

When to use it

  • Data Analysis: Run complex analytical queries to extract insights from large datasets without manual SQL writing.
  • Schema Management: Automate the creation of tables, indexes, or views based on evolving application requirements.
  • Routine Maintenance: Execute maintenance tasks like vacuuming, analyzing, or updating statistics to optimize performance.
  • Development Integration: Connect AI agents to development workflows for rapid prototyping and database testing.

Key capabilities

  • Direct execution of SQL statements against PostgreSQL instances.
  • Management of database schemas, including table creation and modification.
  • Support for standard PostgreSQL administrative commands.
  • Integration with the vibe-coding-cn environment by 2025emma.

Example prompts

  • "Create a new table named 'users' with columns for id, name, and email."
  • "Run an analysis to find the top 10 most active users from the last month."
  • "Optimize the performance of the 'orders' table by updating statistics."

Tips & gotchas

Ensure your AI agent has the necessary permissions to execute administrative commands if you plan to modify schema structures. Always validate generated SQL queries in a test environment before applying them to production data to prevent unintended side effects.