astropy

astropy is a skill for Claude Code, Codex from foryourhealth111-pixel/Vibe-Skills. It costs 84 tokens per session (2,727 once invoked), scanned A, a copy of astropy, Apache-2.0.

A Python library for astronomy and astrophysics, including sky coordinates, physical units, FITS files, cosmology, precise time systems, tables, and astronomical images. FITS is a standard file format used for scientific astronomical data.

In plain words
What is it for?
Use it to transform celestial coordinates, convert units, read or write FITS files, calculate cosmological values, handle astronomical times, work with catalog tables, and map image pixels to sky positions.
Why use it?
It provides common astronomy data structures and calculations in one library, reducing the need to implement coordinate conversions, unit handling, or scientific file processing yourself.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to transform celestial coordinates, convert units, read or write FITS files, calculate cosmological values, handle astronomical times, work with catalog tables, and map image pixels to sky positions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/foryourhealth111-pixel/vibe-skills/astropy
About the project

Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.

foryourhealth111-pixel/Vibe-Skills · 3,770 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add foryourhealth111-pixel/Vibe-Skills --skill astropy
Clone the repo
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for astropy

README.md
[![agentmods](https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/astropy/github.svg)](https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/astropy)
Your own site
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/astropy"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/astropy/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for astropy

Your own site · 80×15
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/astropy"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/astropy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,727 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 84% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.02727
Opus 5.5 $0.00034 $0.01091
Sonnet 5.5 $0.00017 $0.00545
Haiku 4.5 $0.00008 $0.00273

Measured 1mo ago against content hash 94debbfcc5ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

astropy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

84% identical to astropy — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

bundled/skills/astropy/SKILL.md · 329 lines

How it starts

The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Astropy

Overview

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis. Use astropy for coordinate transformations, unit and quantity calculations, FITS file operations, cosmological calculations, precise time handling, tabular data manipulation, and astronomical image processing.

When to Use This Skill

Use astropy when tasks involve:

  • Converting between celestial coordinate systems (ICRS, Galactic, FK5, AltAz, etc.)
  • Working with physical units and quantities (converting Jy to mJy, parsecs to km, etc.)
  • Reading, writing, or manipulating FITS files (images or tables)
  • Cosmological calculations (luminosity distance, lookback time, Hubble parameter)
  • Precise time handling with different time scales (UTC, TAI, TT, TDB) and formats (JD, MJD, ISO)
  • Table operations (reading catalogs, cross-matching, filtering, joining)
  • WCS transformations between pixel and world coordinates
  • Astronomical constants and calculations

Quick Start

import astropy.units as u
from astropy.coordinates import SkyCoord
from astropy.time import Time
from astropy.io import fits
from astropy.table import Table
from astropy.cosmology import Planck18

# Units and quantities
distance = 100 * u.pc
distance_km = distance.to(u.km)

# Coordinates
coord = SkyCoord(ra=10.5*u.degree, dec=41.2*u.degree, frame='icrs')
coord_galactic = coord.galactic

# Time
t = Time('2023-01-15 12:30:00')
jd = t.jd  # Julian Date

# FITS files
data = fits.getdata('image.fits')
header = fits.getheader('image.fits')

# Tables
table = Table.read('catalog.fits')

# Cosmology
d_L = Planck18.luminosity_distance(z=1.0)

Core Capabilities

1. Units and Quantities (astropy.units)

Handle physical quantities with units, perform unit conversions, and ensure dimensional consistency in calculations.

Key operations:

  • Create quantities by multiplying values with units
  • Convert between units using .to() method
  • Perform arithmetic with automatic unit handling
  • Use equivalencies for domain-specific conversions (spectral, doppler, parallax)
  • Work with logarithmic units (magnitudes, decibels)

Read the full file on GitHub · 329 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 329 lines · 84 tokens per session scan A 94debbfcc5ba

Subscribe to this mod's changes

astropy is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,770 stars, last pushed yesterday), licensed Apache-2.0. It adds 84 tokens to every session and 2,727 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to astropy, differing in 10 lines, and is treated as a copy.

Related

Other skills, from other repositories

numpy

Expert NumPy numerical computing assistance covering ndarrays, broadcasting, linear algebra, vectorization, and memory views. Use when writing ultra-fast scientific calculations and array operations in Python.

G1Joshi/Agent-Skills · 37 tokens

paper2code

Converts an arxiv paper into a minimal, citation-anchored Python implementation. Trigger when user runs /paper2code with an arxiv URL or paper ID, says "implement this paper", or pastes an arxiv link asking for implementation. Flags all ambiguities honestly. Never invents implementation details not stated in the paper.

PrathamLearnsToCode/paper2code · 72 tokens

marimo

Assistant for creating, editing, and debugging reactive Python notebooks with marimo. Use when you need to build marimo notebooks, debug reactive execution, add interactive UI elements, or convert traditional notebooks to marimo format. Provides code patterns, utility functions, and best practices for marimo…

nibzard/skills · 61 tokens

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use…

agent-skills-hub/agent-skills-hub · 73 tokens

astropy

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve…

agent-skills-hub/agent-skills-hub · 84 tokens

anndata

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

agent-skills-hub/agent-skills-hub · 63 tokens