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Profiling Tables

Checked
astronomer·vlatest·testing·Apache-2.0

This skill analyzes tabular data to identify patterns and relationships, offering insights for data exploration and understanding.

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 astronomer/agents --skill profiling-tables -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

astronomer

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 astronomer/agents at cbe1141f54.

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

Commit
cbe1141f54
Manifest
skills/profiling-tables/SKILL.md
Scanned
1 file, 143 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 profiling-tables skill enables AI agents to analyze and summarize data from tables, identifying patterns, trends, and key insights. It can extract metadata such as column types, value distributions, and relationships between fields, making it useful for understanding the structure and content of tabular datasets.

When to use it

  • To quickly understand the contents and structure of a new dataset before further analysis.
  • When preparing data for visualization or modeling by identifying missing values or inconsistencies.
  • During exploratory data analysis (EDA) to generate summaries that guide decision-making.

Key capabilities

  • Extract metadata from tables, including column types and value distributions.
  • Identify patterns and relationships between fields in the table.
  • Generate high-level summaries of dataset contents for quick understanding.

Example prompts

  • "Analyze this table and summarize its structure and key insights."
  • "What are the most common values in each column of this dataset?"
  • "Identify any missing data or inconsistencies in this table."

Tips & gotchas

  • Ensure that the input is a well-formatted table for accurate results.
  • This skill may not handle very large tables efficiently, so consider sampling or chunking data if needed.