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.
npx skills add beita6969/ScienceClaw --skill astropy-astronomygit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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.
[](https://agentmods.dev/skills/beita6969/scienceclaw/astropy-astronomy)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/astropy-astronomy"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/astropy-astronomy/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.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/astropy-astronomy"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/astropy-astronomy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.01064 |
| Opus 5 | $0.00022 | $0.00532 |
| Sonnet 5 | $0.00009 | $0.00213 |
| Haiku 4.5 | $0.00004 | $0.00106 |
Grade A, and why
astropy-astronomy 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Astropy Astronomy
Astronomical computations using Astropy.
When to Use
- Celestial coordinate transforms (ICRS, Galactic, AltAz)
- Unit conversions for astronomical quantities
- Reading, writing, or inspecting FITS files
- Cosmological calculations (distances, ages, lookback times)
- Time system conversions (UTC, TAI, TDB, MJD, JD)
When NOT to Use
- Telescope control or instrument automation
- Real-time observation planning or scheduling
- Image reduction or photometry pipelines (use photutils)
- N-body simulations
Coordinate Transforms
from astropy.coordinates import SkyCoord, EarthLocation, AltAz
from astropy.time import Time
import astropy.units as u
coord = SkyCoord(ra=10.684*u.deg, dec=41.269*u.deg, frame='icrs') # M31
coord_str = SkyCoord('00h42m44.3s', '+41d16m09s', frame='icrs')
# ICRS to Galactic
galactic = coord.galactic
print(f"l={galactic.l:.4f}, b={galactic.b:.4f}")
# Angular separation
c1 = SkyCoord(ra=10.684*u.deg, dec=41.269*u.deg)
c2 = SkyCoord(ra=11.0*u.deg, dec=41.5*u.deg)
sep = c1.separation(c2)
# AltAz (horizontal) coordinates
location = EarthLocation(lat=34.05*u.deg, lon=-118.25*u.deg, height=100*u.m)
time = Time('2026-03-15 03:00:00', scale='utc')
altaz = coord.transform_to(AltAz(obstime=time, location=location))
print(f"Alt={altaz.alt:.2f}, Az={altaz.az:.2f}")
Unit Conversions
import astropy.units as u
d = 10 * u.pc
print(d.to(u.lyr)) # parsecs to light-years
wav = 21 * u.cm
freq = wav.to(u.GHz, equivalencies=u.spectral())
wavelength = (13.6 * u.eV).to(u.nm, equivalencies=u.spectral())
FITS File Handling
from astropy.io import fits
with fits.open('image.fits') as hdul:
hdul.info()
header = hdul[0].header
data = hdul[0].data
hdu = fits.PrimaryHDU(data_array)
hdu.header['OBJECT'] = 'M31'
hdu.writeto('output.fits', overwrite=True)
Cosmological Calculations
from astropy.cosmology import Planck18 as cosmo
z = 1.0
d_L = cosmo.luminosity_distance(z) # luminosity distance
d_A = cosmo.angular_diameter_distance(z) # angular diameter distance
age = cosmo.age(z) # age of universe at z
lookback = cosmo.lookback_time(z) # lookback time
H_z = cosmo.H(z) # Hubble parameter at z
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.
- 11d ago First seen · 121 lines · 43 tokens per session scan A 283e05aa30d8
astropy-astronomy is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 43 tokens to every session and 1,064 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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