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Natural Language Postgres Presentation

Checked
rebyteai-template·vlatest·database

Generates clear, natural language presentations of PostgreSQL data based on user queries and specified formatting preferences.

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 rebyteai-template/rebyte-skills --skill natural-language-postgres-presentation -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

rebyteai-template

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 rebyteai-template/rebyte-skills at 0062e44684.

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

Commit
0062e44684
Manifest
natural-language-postgres-presentation/SKILL.md
Scanned
1 file, 56 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 query and present data from a PostgreSQL database using natural language. It translates user requests into SQL queries, executes them against the database, and then formats the results into a readable presentation. The agent can handle complex queries involving multiple tables and conditions.

When to use it

  • Generate reports: Quickly create summaries of sales figures or customer demographics without writing SQL manually.
  • Data exploration: Allow non-technical users to explore data stored in PostgreSQL through conversational prompts.
  • Dashboard creation: Build interactive dashboards by dynamically querying and displaying data based on user input.
  • Ad-hoc analysis: Answer specific questions about the database content, such as "What were our top 10 selling products last month?".

Key capabilities

  • Natural language query processing
  • SQL query generation
  • PostgreSQL database connectivity
  • Data presentation formatting

Example prompts

  • "Show me the total sales for each product category."
  • "List all customers who placed an order in the last week."
  • "What is the average order value?"

Tips & gotchas

  • Ensure the AI agent has appropriate database credentials and access permissions.
  • The accuracy of results depends on the clarity and specificity of user prompts.