Astropy Repo Skill

SkillDev tools

"Use Astropy core for astronomy units, coordinates, times, tables,

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Astropy Repo Skill skill

What this skill tells your AI

The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/astropy/SKILL.md and read by ahel’s review.

Use this skill when a task needs the Astropy core Python package for astronomy or astrophysics analysis. Astropy is a CPU scientific-Python library; selected workflows do not require GPU or accelerator backends. Use an installed Astropy package and the bundled references/scripts here rather than reopening the source repository.

Fast Start

import astropy
from astropy import units as u
print(astropy.__version__)
print((42 * u.km / u.s).to(u.m / u.s))

If plotting, fitting, convolution FFT paths, or common dataframe bridges are needed, prefer installing the common optional set:

python -m pip install "astropy[recommended]"

Use astropy[all] only for broad optional integrations such as HDF5, Parquet, S3/fsspec, Jupyter, or additional astronomy packages.

Route by Task

Shared References and Scripts

Operating Rules

  1. Keep units attached until a non-Astropy API requires raw arrays; then use .to_value(unit) and record the unit.
  2. Be explicit about format=, scale=, frame=, unit=, origin=, and format names for I/O to avoid silent guessing.
  3. Use temporary files for smoke checks and never mutate user FITS/table files unless the user explicitly requested that exact operation.
  4. For offline or reproducible tasks, disable or control remote downloads before coordinate/time/IERS/name-resolution operations.
  5. Validate scientific transformations numerically: unit round-trips, pixel/world round-trips, table read/write round-trips, fit residuals, or cosmology unit checks.
  6. Route optional dependency errors to the nearest sub-skill first, then to the root troubleshooting reference for install-level decisions.

Do Not Use This Skill For

  • General NumPy/Pandas data processing without Astropy APIs, astronomy formats, units, times, or coordinates.
  • Maintaining the Astropy repository, release engineering, CI, or documentation build workflows.
  • Running broad Astropy test suites or benchmarks as a substitute for a focused user workflow.
  • SAMP services, remote data downloads, or file-mutating CLI operations without explicit user approval and bounded temporary-file safeguards.

Signals

GitHub stars
266
Forks
21
Last commit
Sep 2026

ahel review

  • K1binfo
    installs-packages
  • K6low
    bundled executables the agent is told to run
  • K1binfo
    installs-packages (in references/package-overview.md)
  • K1binfo
    installs-packages (in references/troubleshooting.md)
  • K1binfo
    installs-packages (in sub-skills/cli-config-data/references/operations.md)

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
astropy-vectorspacelab
Source
github.com/vectorspacelab/arex-skill