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Postgres

Checked
thinkfleetai·vlatest·database

Automates PostgreSQL database tasks like backups, query optimization, and schema management using intelligent AI insights.

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 thinkfleetai/thinkfleet-engine --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

thinkfleetai

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 thinkfleetai/thinkfleet-engine at 1256c5192f.

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

Commit
1256c5192f
Manifest
skills/postgres/SKILL.md
Scanned
1 file, 39 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 allows AI agents to interact with and query PostgreSQL databases. It enables retrieving data, executing SQL commands, and managing database connections directly within an agent workflow. The skill provides a streamlined way to integrate database operations into automated tasks and information retrieval processes.

When to use it

  • Data Extraction: Automatically pull specific data from a PostgreSQL database for reporting or analysis.
  • Automated Database Updates: Modify database records based on external events or triggers.
  • Application Integration: Connect an AI agent to existing applications that rely on a PostgreSQL backend.
  • Complex Querying: Execute sophisticated SQL queries to retrieve and process data from relational databases.

Key capabilities

  • Connects to PostgreSQL databases
  • Executes SQL queries
  • Retrieves data from tables
  • Manages database connections

Example prompts

  • "Retrieve all customer records from the 'customers' table."
  • "Execute the following SQL query: SELECT * FROM products WHERE price > 100;"
  • "Update the 'orders' table to mark order ID 123 as shipped."

Tips & gotchas

  • Ensure your AI agent has the necessary database credentials and connection details.
  • Be mindful of potential security implications when executing SQL queries; sanitize inputs to prevent injection attacks.