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Astropy

Checked
drshailesh88·vlatest·frontend

Astropy provides a streamlined frontend for astronomical data processing and visualization, simplifying complex calculations & displays.

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 drshailesh88/integrated_content_os --skill astropy -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

drshailesh88

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 drshailesh88/integrated_content_os at 9e61937ad2.

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

Commit
9e61937ad2
Manifest
skills/scientific/astropy/SKILL.md
Scanned
8 files, 2,443 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, drshailesh88-astropy, provides access to the Astropy Python library. It enables AI agents to perform astronomical calculations, manipulate celestial data, and work with various astronomical file formats. Specifically, it allows for tasks like calculating distances between stars, converting coordinate systems, and analyzing astronomical images.

When to use it

  • Researching Astronomical Objects: An agent needs to determine the distance to a newly discovered exoplanet.
  • Data Analysis: An AI is processing data from a telescope and requires tools for calibrating and analyzing image data.
  • Simulations: You're building an astronomical simulation and need accurate calculations of celestial mechanics.
  • Educational Applications: An agent needs to explain astronomical concepts like coordinate transformations or light curves to a user.

Key capabilities

  • Access to Astropy Python library functions.
  • Celestial coordinate transformation.
  • Astronomical data file handling (e.g., FITS).
  • Distance calculations in astronomy.

Example prompts

  • "Calculate the distance between Vega and Sirius in parsecs."
  • "Convert the coordinates of this star from J2000 to Galactic coordinates: RA=18h45m39.6s, Dec=+0°17'47".
  • “Read the FITS file ‘image.fits’ and display its header information.”

Tips & gotchas

  • Requires a Python environment with Astropy installed. Ensure the agent has access to this environment.