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Postgres

Checked
sundial-org·vlatest·database

Connects to and queries Sundial Organization's PostgreSQL databases for data retrieval and analysis.

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 sundial-org/awesome-openclaw-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

sundial-org

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 sundial-org/awesome-openclaw-skills at b80cde2ef8.

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

Commit
b80cde2ef8
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 PostgreSQL databases. It enables querying data, executing SQL commands, and managing database connections directly within an agent workflow. The skill provides a standardized interface for accessing and manipulating relational data stored in PostgreSQL.

When to use it

  • Data Analysis: An agent needs to extract specific information from a customer database to generate reports or identify trends.
  • Inventory Management: An agent must update product quantities in an inventory system based on sales data.
  • Order Processing: Automating order fulfillment by retrieving customer details and updating order statuses within a PostgreSQL database.
  • Content Retrieval: An agent needs to fetch articles from a content management system (CMS) that stores its data in a PostgreSQL database.

Key capabilities

  • Connects to PostgreSQL databases.
  • Executes SQL queries.
  • Retrieves and manipulates data within tables.
  • Supports standard SQL commands.

Example prompts

  • "Retrieve all customer names from the 'customers' table."
  • "Update the product quantity for item ID 123 to 50 in the 'inventory' table."
  • “What is the average order value from the last month, based on data in the orders table?”

Tips & gotchas

  • Ensure your AI agent has the necessary database credentials (hostname, username, password) configured.
  • Be mindful of SQL injection vulnerabilities when constructing queries dynamically; sanitize user inputs appropriately.